{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Building our operators: the Face Divergence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The divergence is the integral of a flux through a closed surface as that enclosed volume shrinks to a point. Since we have discretized and no longer have continuous functions, we cannot fully take the limit to a point; instead, we approximate it around some (finite!) volume: *a cell*. The flux out of the surface ($\\vec{j} \\cdot \\vec{n}$) is actually how we discretized $\\vec{j}$ onto our mesh (i.e. $\\bf{j}$) except that the face normal points out of the cell (rather than in the axes direction). After fixing the direction of the face normal (multiplying by $\\pm 1$), we only need to calculate the face areas and cell volume to create the discrete divergence matrix.\n",
    "\n",
    "<img src=\"images/Divergence.png\" width=80% align=\"center\">\n",
    "\n",
    "<h4 align=\"center\">Figure 4. Geometrical definition of the divergence and the discretization.</h4>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementation\n",
    "\n",
    "Although this is a really helpful way to think about conceptually what is happening, the implementation of that would be a huge for loop over each cell. In practice, this would be slow, so instead, we will take advantage of linear algebra. Let's start by looking at this in 1 dimension using the SimPEG Mesh class. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d90b290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from SimPEG import Mesh\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "plt.set_cmap(plt.get_cmap('viridis')) # use a nice colormap!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10d9adb50>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dsBdJkiRpZAYN1muBW5rXtwAX9KlZBWypqq1VtQu4rTlvj08Bvz1gH5IkSdJIDRqsj6yq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\nUgsM1pIkSVIL/j9gZTUNeX+dFAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x103dbd2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define a 1D mesh\n",
    "mesh1D = Mesh.TensorMesh([5]) # with 5 cells \n",
    "\n",
    "fig, ax = plt.subplots(1,1, figsize=(12,2))\n",
    "ax.plot(mesh1D.gridN, np.zeros(mesh1D.nN),'-k',marker='|',markeredgewidth=2, markersize=16)\n",
    "ax.plot(mesh1D.gridCC,np.zeros(mesh1D.nC),'o')\n",
    "ax.plot(mesh1D.gridFx,np.zeros(mesh1D.nFx),'>')\n",
    "ax.set_title('1D Mesh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The flux on the faces is [ 0.  1.  2.  2.  1.  0.]\n"
     ]
    },
    {
     "data": {
      "image/png": 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d70bznFmNRdro7qAcUzWwpEllVfGIEaoqTgutCeSUegNLWpV7Fc+dG9ytJvXTR0nLRyxf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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x103dbd810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# and define a vector of fluxes that live on the faces of the 1D mesh\n",
    "face_vec = np.r_[0., 1., 2., 2., 1., 0.]  # vector of fluxes that live on the faces of the mesh\n",
    "print \"The flux on the faces is {}\".format(face_vec)\n",
    "\n",
    "plt.plot(mesh1D.gridFx, face_vec, '-o')\n",
    "plt.ylim([face_vec.min()-0.5, face_vec.max()+0.5])\n",
    "plt.grid(which='both')\n",
    "plt.title('face_vec');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Over a single cell, the divergence is \n",
    "\n",
    "$$\n",
    "\\nabla \\cdot \\vec{j}(p) = \\lim_{v \\to \\{p\\}} = \\int \\int_{S(v)} \\frac{\\vec{j}\\cdot \\vec{n}}{v} dS\n",
    "$$\n",
    "\n",
    "in 1D, this collapses to taking a single difference - how much is going out of the cell vs coming in? \n",
    "\n",
    "$$\n",
    "\\nabla \\cdot \\vec{j} \\approx \\frac{1}{v}(-j_{\\text{left}} + j_{\\text{right}})\n",
    "$$\n",
    "\n",
    "Since the normal of the x-face on the left side of the cell points in the positive x-direction, we multiply by -1 to get the flux going out of the cell. On the right, the normal defining the x-face is point out of the cell, so it is positive. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The face div of the 1D flux is [ 5.  5.  0. -5. -5.]\n"
     ]
    }
   ],
   "source": [
    "# We can take the divergence over the entire mesh by looping over each cell\n",
    "div_face_vec = np.zeros(mesh1D.nC) # allocate for each cell\n",
    "\n",
    "for i in range(mesh1D.nC):  #  loop over each cell and \n",
    "    div_face_vec[i] = 1.0/mesh1D.vol[i] * (-face_vec[i] + face_vec[i+1])\n",
    "\n",
    "print \"The face div of the 1D flux is {}\".format(div_face_vec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Doing it as a for loop is easy to program for the first time, \n",
    "but is difficult to see what is going on and could be slow! \n",
    "Instead, we can build a faceDiv matrix (note: this is a silly way to do this!)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The 1D face div matrix for this mesh is \n",
      "[[-5.  5.  0.  0.  0.  0.]\n",
      " [ 0. -5.  5.  0.  0.  0.]\n",
      " [ 0.  0. -5.  5.  0.  0.]\n",
      " [ 0.  0.  0. -5.  5.  0.]\n",
      " [ 0.  0.  0.  0. -5.  5.]]\n",
      "\n",
      "The face div of the 1D flux is still [ 5.  5.  0. -5. -5.]!\n"
     ]
    }
   ],
   "source": [
    "faceDiv = np.zeros([mesh1D.nC, mesh1D.nF]) # allocate space for a face div matrix\n",
    "for i in range(mesh1D.nC):  #  loop over each cell\n",
    "    faceDiv[i, [i, i+1]] = 1.0/mesh1D.vol[i] * np.r_[-1,+1]\n",
    "\n",
    "print(\"The 1D face div matrix for this mesh is \\n{}\".format(faceDiv))\n",
    "\n",
    "assert np.all( faceDiv.dot(face_vec) == div_face_vec )  # make sure we get the same result! \n",
    "\n",
    "print \"\\nThe face div of the 1D flux is still {}!\".format(div_face_vec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the above is still a loop... (and python is not a fan of loops). \n",
    "Also, if the mesh gets big, we are storing a lot of unnecessary zeros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'There are 20 zeros (too many!) that we are storing'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"There are {nnz} zeros (too many!) that we are storing\".format(nnz = np.sum(faceDiv == 0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Working in Sparse\n",
    "\n",
    "We will use instead *sparse* matrices instead. These are in scipy and act almost the same as numpy arrays (except they default to matrix multiplication), and they don't store all of those pesky zeros! We use [scipy.sparse](http://docs.scipy.org/doc/scipy/reference/sparse.html) to build these matrices. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import scipy.sparse as sp\n",
    "from SimPEG.Utils import sdiag # we are often building sparse diagonal matrices, so we made a functio in SimPEG!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the sparse differencing matrix is \n",
      "[[-1.  1.  0.  0.  0.  0.]\n",
      " [ 0. -1.  1.  0.  0.  0.]\n",
      " [ 0.  0. -1.  1.  0.  0.]\n",
      " [ 0.  0.  0. -1.  1.  0.]\n",
      " [ 0.  0.  0.  0. -1.  1.]]\n",
      "\n",
      " and the face divergence is \n",
      "[[-5.  5.  0.  0.  0.  0.]\n",
      " [ 0. -5.  5.  0.  0.  0.]\n",
      " [ 0.  0. -5.  5.  0.  0.]\n",
      " [ 0.  0.  0. -5.  5.  0.]\n",
      " [ 0.  0.  0.  0. -5.  5.]]\n",
      "\n",
      " but now we are only storing 10 nonzeros\n",
      "\n",
      " and we get the same answer! [ 5.  5.  0. -5. -5.]\n"
     ]
    }
   ],
   "source": [
    "# construct differencing matrix with diagonals -1, +1\n",
    "sparse_diff = sp.spdiags((np.ones((mesh1D.nC+1, 1))*[-1, 1]).T, [0, 1], mesh1D.nC, mesh1D.nC+1, format=\"csr\")\n",
    "print \"the sparse differencing matrix is \\n{}\".format(sparse_diff.todense()) \n",
    "\n",
    "# account for the volume\n",
    "faceDiv_sparse = sdiag(1./mesh1D.vol) * sparse_diff  # account for volume \n",
    "print \"\\n and the face divergence is \\n{}\".format(faceDiv_sparse.todense())\n",
    "\n",
    "print \"\\n but now we are only storing {nnz} nonzeros\".format(nnz=faceDiv_sparse.nnz)\n",
    "\n",
    "assert np.all(faceDiv_sparse.dot(face_vec) == div_face_vec) \n",
    "print \"\\n and we get the same answer! {}\".format(faceDiv_sparse * face_vec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In SimPEG, this is stored as the `faceDiv` property on the mesh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 5.  5.  0. -5. -5.]\n"
     ]
    }
   ],
   "source": [
    "print mesh1D.faceDiv * face_vec # and still gives us the same answer!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Moving to 2D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To move up in dimensionality, we build a 2D mesh which has both x and y faces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Mex+EDJkHj2F/U3u+uSLoVL8W246n416/FvOt2XS1aLFmY2lqgjDGGLM7vMVkjDGzRniL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\n/3/PQrNCJpyjAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10dc1bfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mesh2D = Mesh.TensorMesh([100,80])\n",
    "mesh2D.plotGrid()\n",
    "plt.axis('tight');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We define 2 face functions, one in the x-direction and one in the y-direction. Here, we choose to work with sine functions as the continuous divergence is easy to compute, meaning we can test it!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 8080 x-faces and 8100 y-faces, so the length of the face function, j, is 16180\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x110e894d0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xIx6hiG5ycTL0oZXByoWrzkHJa7sofXsv0ZMzSLtyBoZR/vkOPXXR6dbVhtfJ\nhc/toemtj2n9fAvRly/BPmtqp1woboGzqIiq558jatYZRJ9xFkKIThlQ3f7yw+Wv/wODxU7KOVf4\n9+vekUrgFuq//t4XfkneBbdiiYxn+xM/GJakoW0l6X0fCEzLLBvy9YaKU9IytyVmU7Xzk16PUQwG\n0i6+nqJn/4I1OR1L3sAKb1knjCVlQjZNqz+i4p4/E7vifGxzJg3YSjVFhTHq2hmMWT6Ris8KOfDE\nZg48qjHm2knkLcwaUNgkNieS+T+ZxpzbJ3LwvWLW/XEbUpOMvzyPvAtzMIcPj7stVIXo2flYp46m\n/sMdFN37L8Im5xG7/CyMsX3XTu+zf6GQtGQZ5S88SvVn75K4YEnI41STBdFDoopqsuJ1tXVrb687\njjUmmbSLb8No63msbeVF1Hy5loybvochzN6vYIjUNBpeew9PdRXh58zBNmsSqmV4jaHaPVUcfH4n\ntftqGLtsHHN/MA1LpN9iFcrAE5MGitayRg6+sIsTnx8l5dzRTH3oGqwp/lyFtn4mDbXvP0r9s6sx\nZaaS/LM7MER2zTdo3riR+g8+IOGqqwjP7m6xA9R++RHetlbSF6/o1zPnbm1Aal7MEUMrwHYyPPLf\nl4syVJySytwSnYDmbMPT1oIxrGdX2hgRTcqSa6j69G2SE1ZiihxY5qdiNhF91fnYZk+m4dV3afls\nO3E3X4wxo+9kmJOhGlXSz80n7Zw8GrcWceCFXex9fAvjlo8nd2k+Zlv/XxImm5GJV+RRcFk+FTtq\n2PvKYTY9tocJy/IZd0kuloSBjy8UhKoQu3gaUWeOp/Llryj5wSNELZpB+OL5KNYB0jxOgmIwkHrl\nSkqf+hum6Dhix80e0Pmq0Yzb0ditvbWiEHvqKMwR/mqOoZS0t7WZ8jefI+WCqzFFh6iNHgJaq4Pa\nx18EVSHuO1eh2jrmQYauYKWUVH9VytEXt9FW1UrBtROYd998DBZDF4/t60RzaSN7nt7Fia9Kybpi\nCvNeXIEpytrFY+sLWksb9S++T/veQmKuu4iwKeO6eGzS66Xu1TdwHS0i9bbbMMbHQ4gM0JYje2nY\nuZHs6+/orBvfFxwnirElZg17huipFDM/pcIs4+/4U+dEeMVHr2DLGUtE7nhAV91OJ3sd23XrP6H1\nwC5Sb7kNadelJ+sShDpZCTp3WtUXR1JdNLzzFfWrN5Bw5RzilswkTFd8y6pzo8MCDIUwHVMhzBDc\n3/GANu5IlwXjAAAgAElEQVQ/wbZnD1C5o5rJy3KZclUu1igzBtERZul/bZbGKidb/3mU3atLGL0w\nnZk3jsUcH1Tqete6Y7vNG7Tk27zGbtvtnuD+do8Bd3UTJ57/lJZdJSTeciGWyeM792s9hFxwB13r\nDuhrd3hP1HDi9X+SeO4lWFP9bryiswA7aNhdogkSGvZtxlFeSNrCqwMH+D+OPvcHkhdeSViyv2Jk\nKLkof+0ZzIkpxC5Y2Nmur71zsly4yyupeeRZwmaMJ+qKRRh01rgxwGgy60IrVh1zpUMuusqCf1v6\nJLUbjrD76Z1IKZlyfQE552Rh1TGnutTv6UEu3G1etr9SxORLMrFEmLrIhYaezRIIs+jCa9XFbex4\nejdlXxxnzJUFjFk2Dq8lGHLqj1xIKWlct5+KJ9cSPqeAqMsXdr7sO+TC29BE7YP/RLHbibvuahSL\nn1Z2sly4qk5Q8cTDpCy/EWt6VhdZ6E0uKj55HVN4NHHTFwCw98/DE2ZZV9S/ZePmZReOhFkGC0N4\nFG1lhZ3KvDfEnL4A14kyat58jdjlVw7q7S1UlZiL5mKfOYbqx96kcf1+cu9YRFh2/yY1QyFxfBzn\n/+EMGoqb2ffKQZ655H2mXJXHzOtGYbYNLFkiPDGMBXdM5LTrR/PVs0d4/soPyT0vk2krxxGeNDyT\npaaESDLuvJiGPZVU/m01YduPEbvifMQQko9MsfFEzZzLifdeJeum7/e73rdiNONzd51987Y78La1\nYk1I6/XchAsuQ7X1j77m2Lqb+n+uJubaJdhmd1B/h26NNxysYccD64lIszPlW9NInZuGpTPbs38M\nGE+7lx2vFrHxmSNkTItl3KI0LP10yhpLm9ny5D5KvqigYNlYlq2eiQzzexveATgDnrpmyv/+PorZ\nQOqPr8aan4bnJJ65q7CM2qdexT5jMhGLFiC8oeVFa3NQtepF4hddhDU9q/+DANoqiohaMHVA5/QH\nPVFu/xtxSilzry040WXOHUXN2jfxBp7JjvaulnnQgoq97koq/vwgzZu/IPzMOf5zdFa4CKRgh6p+\nCGA1B6zt7HCS/ngl1e/v5uBP/kXaRRPJvmYGdp0112GF23TWuFVnVlhVf3uHhR6VZyD/nrHUr8jg\n04cP8cSSD5h3Yw5zr0rHGKjD3d+JrsgEuPDOfBaszGTDs0WsWv4e4xamMf3GsUQk+R/W9sBscNey\nu72X4FWVoDWmTkoi+m8rOfbHd6j81ROk/vAKDJHB5B2vjscsO2pc65W0flkwj8A6ayoNW76keuMa\nYs9d3NUC6xjCSROgMtyEJt14A+8pqYCjpgJDbBxapK4cbgi5IDI8oI4lMiAjelnpkIvmjzbQsnY9\nCXetxDY6EfAPLJRc6Cc1w0J6af42V5OTvY9vouSzUqZ/ZyoTl2YGSiy4uskFgFHoyyT7231OL5te\nKeOzp4rInBzJLU9OJWV0OP48+bYeJ0A9PgMNx9vY9FwRe98rZ8byHM778UIsESbAS7vmDFynb7mQ\nUlLx3j6OPPEFyUunknrVLFxYADftOi+ybv026l5YQ8ItF2GeOMF/zz3BPjvkQmoa1S8/hyV/FGGz\np+INTPIqnuD4e5ILn8eNsJhRs1LxDnPC6KkUZjmllLkeltR0XDVV+FxOFHPvWZfgTzNPvPkGKv7y\nEMbUJCy5OYO+thCCxPMnkTwnnUN//YS9v13D6OWTiB47tMVkY9JtXPbbqdQVNvDRQ0f44rkizrpl\nFDMuTcM0wBC1LcbMWd8v4LQVuWx67iiv3/4FWXMSmPPNgq7rZQ4Sqs1C6l3LqF/9BSU/foKE267A\nOn5w91QIQcyCc6h89klMiUlEjp3S5zmKqbtl7q6twhw/PAv6Nq9dT+uGrST9/FYMUREMlW7o03wc\ne/sQex7fRs45GVz2ysWYI8wIpZ+zioDHpbH11XI+f7KQtPGR3PjINNLG9c/DaG/28Mnjh9n+eilz\nbsrnO++cgyXC1CX81l+0n2jiwB8/xtPipOD3y7DlBLxT3VeRmkb1Pz6kddsRUn9xI6a0BLy90Bgb\nXn0LoSrELL1gwNR8V3UlPrcL1Tj8qf+aHLHMv3YoBiOW5DTay0qw5faPW2qMiyNuxTJqn3qRpLtu\nR00a2kShJd7OxF8t4cQnh9j043fJvGAs+StnDvmuJuWFc+1fp1K5t5E1fzvCumeKWPS9XCYtTupc\nrLm/6FDqk5bn8/lf9vD0pWs4/c7p5CzoPRTRHwhFIfayM7CMSqHir68QeeFcopZ054T3a5xjxoGq\nUvXSCzjG7iJxyeW9hkIUowmfp2vVOndtFaa4oSvztq17aPlgHYl3fzugyIeGhv1V7PvLZygGlfl/\nWUzauN757ydDSsm+NRXsebcMJFz/0FTSCjqYOr1rPq/bx+ZVpXz6eCGj5yfx7dfnY40fXNhN+iTF\nq/dw8OktZF41jYwrp+H0dTekvM0OKh54FWFQSf31t1DtvSfutaz7kvaDR0m943Z/stZAlfmJCsyJ\n/UsQGyh8I5b51wOvraPKnh/m3GwclYWYJ+bTwSCSBt1Elm6bgBttnZ5HeNUcal94icQfrUAx+d/m\nxhCLCFi6TGoFt20BN9oe+IxcnM2Y2dFsvv9LNnzjJc6+dzbx42KxqjrXW0ekDut0p4P7u7jTge2Y\nSUYKnhrHkS2NbFhVyRfPFnH1z3IYNdmvYLQu7nRw2xNYcktPq7IkGVn+uwkc21zHm/ft5PBbh5l3\n13Qi0/wK06C7fl+LY5y8mnvYrHQs6TdT9vtV4Ggh5qpzOzMoPYG1wvSruPv0dMxAGr80ClS7Ha2p\nidZD+3AUHiL+qqsILwjU9PfpeOoSfJFGDHGxwTCLAFd9Ndbx4/CG6UIm/ZQLjP7QQd0zr+HYvIvk\nn96CKTUCo7l7aCWUXNh0oZUOufB5fRx5ciNV2yqZuCyP/PNzEIrAqlu9oy+5qCts4rVfH8bR4OGK\nn44if0Z0YALUT8tUQ4TfNKkgpWTn2jpef6CI+Ewr339mIvF5kYAPjwxSOl26+FOH3Bl8elnwbzeV\nt7D7od04qhzMf/RiwjOjAQ+tujCIEBJHYTWl975J9BljSVlxJi7NSIdX07FEXodMALQdPELje2tJ\n+r9vQYwZH75OmQC/XHTA59Vdq3N6QdBeV4ExPbVTFoYTbnnqqMhTZ6QhYM3OoeGTjwd8XsT5Z+Kp\nrqXu6TeI++blw0JnssaGMe93Z1P84THe//6njL0kl7nfHINqHDpPNW9GFPnTw9n0Vg2P3HaQcadH\ncdmdWdjj+g4vnYycmbHcvOosNj13hH9dt5Ypy/OZdv0YGEStbz2M8ZFk3nc9Zb99mapH3yLx1osG\nvHixarehNTWBpoEQuMvKoCD0alvCYMRVXtalzV1dhTFh4Ja55mijdeNmmt//HF+LA/O4HMzZQys+\n5mxoY8svPkJVJPP/cC6x8QO7F06Hl7V/L2TbmxUs/HY2c69KxdLPyo0l+1tYdV8hTofGsp/nMXau\nfz6jp3KuvUFKyYHXjrDl0V2Mv2kqcy8dg5PQcle77hBVa/aQsuJMYuYX+Bt7mSv2nKij9rGXiP/W\n1RgT47qEaQaCtsMHiRs/YXAn94FTaQL01BlpCFgys/C53fg8A5MCIQQxy5fiOV5N8zvrhm08Qgiy\nF47isn+eT93hBv51zVqqD9YPS9+KIph9cQK/+mAqETFG7r1wO2ufLsfrHqBPCqhGhTk3jebqF8+j\nal89L165hqrd1UMeo2oxkXH3MjwVtdQ+t4aB0l4Vmw0UBRSF5FtvJeaCC3o8Vqiqv1xtAFp7O9Kn\nYYgc2GIczZ9soPxH99G0ei2+FgcoCvHfDF2tsb+o23OCT298lZjxiZz1l4VYovtfAVNKyY53KvnD\nBV/gaPTwk7dOY9616aj9SC5ra/Hyz18W8site5l7RRL3vD61U5EPBq3Vbbz33U84+NZRlj5xHmOu\nGIeidh+H9EmOPrWR4sc+I/OGM4KKvBdojnZqn15N1GXnYRnbP/pfyDHu24O3vg5fW/cEsuGAJkW/\n/v4bcEpZ5l6TG2lQg5a0zQwGQVtVMZYxAYHQu9BdtgMrnwdYK6pFJfXuqyj7yRNYs2MIn+Mvlaqv\nbqdnJdhCMBTsRifN5c1YY6xE6bjHtmTBsgdP4+h7x1j/+63kz0vkvG+kowRYHJZAWqOljzBLVz6x\nfzsyEm66O5HFyyJ55lflbHy1gut/ms74M4IJUR3hFX2YxSmClneHG2/OMJP10DQOfnqCN3/4GdOv\nzWPWytEYO8MswTEpuhTyzjCMzsXvrBFihpx7l3H0rmco+9FR0v7fjajhYXh1RbU0Vf+7+JWDzyuw\nz5tB2GkTaf1yG+72BozWDIQW+K11LwYh/UweqXnRwvxjcDfWoYTb8NnpsuJBB5umJ7kwj81AmAzI\nNn/oQ42wEZYWRoeZaA7IQ19yEWbwIKWk8NW9HHxuG3PvmUv6GenYVf+sn80QnP3rGloJtreUNvHa\nb4/QXO3i1r+OJndqREAW/IqqJ7mQUvLluw0899vjTDsrkj++W4A90gC0dw2/9VMuTF4Pu985zpo/\n7mPKVbnMunE0qlHB4fUvEaSXC83hYvMvP8HT4uL0x6/AHB2GwxP8TvraMc6O8IrmoepvzxM2Kpmo\n86bRYb53yoXuxaUPrdAlzCLw1tdT/fKL/r4ri7Gd1uuayYOCdgrZu6fOSIHSn/8Sn6PrG9ian4fz\n8NFB9WeMjSD5rmVUPfwWzuKqQfVR+G4h7970Lo2lzV3ahRBMWpLOFX+YxrGvanh4xRbqyobPekjJ\nsfCTp/K45q403nzsBH//wVFaGgbnp45ZkMT1L51N4boTvHr7F7Q39lE9qQ+odiup312Kq6SGwhvv\np/y+53FsP4j09s7Pts2cTPgZpxEx/3Ta9x3q9VihqkgdIdrb1IQhauBL5JmzU4m75UoQAoTAOmlg\nZR86r9/mYfO9H1P87kEueOoC0s/oX00P8FvjW14/zp+u3s74s+L46WuTyZ3av4nXEyUufrPyKKsf\nOcGdD2Zzy68yAop8cGitd/PyD7ay4emjXPvIacz95lhUY2g10VzazCe3rMYaF8a8v16IObrv6qBS\nSk488haq3UrcdecNepzS66XqkaeQAa/csWvPoPvqDT6p9OvvvwH/HaPoJxSLBZ+za/6vJT8X56HB\nKXMAa14a8Tcupvi+VXibelz6qUdMvmUyY68Yy2s3rqVo3fFu+yOTrKx4YjYTz0vkwas2sfm14wMO\nP/QEIQTTzo7ix0/kEhln5CcX7mXr2oZB9RWRGMbVT84jLjeSVde8T+XumiGNzT4mDVNKDPgkbTuO\nUv3Xf1H2gz/367uHTSygbecetJbWHo8RBkPXMEtTc7caIP2B9Go0vr6W2OsvwDImk/DTB7wmAK6G\nNrb+7jMUk8qCxy4hPLX/bJW2Jg8v/GA3654t4fZ/TOb0K1M7Pbje4HH5eP3vFdxz+UEmnB7B794Y\nS/7UodXxPvB5Davu2UtMuo1bXjqDlHE9vxyPbzzOe7e8R+7l45n6o3ko/Zwbqn55Pe7jtSR971JE\niJBNf9G87gs8VdWdHpvW2Ii3sXt5h6FCQ+nXXygIIZ4SQlQJIXb3sH+5EGJX4G+DEGKibt8iIcRB\nIcRhIcSP+zPWUyrMIqxmNNmOag24mUJiLMjA/WQFPtr8KcQ6F17RrcvZsUanQVfd0BxIxbaeMwbl\nRAXl97/C5N9fjGr2u572LgyFoLXakQxkC7jIM67MJL/AxOs/3EzToUwWfScLRRFd3OmlN8Yz7fQw\nnvzhIY59XsHK+7KJ1NUEMnUJs/jH1cWdDrGwbCdtyg63/SyOBYus/OWuEravqeHmn6cSFhkkp5t1\n7rRFBhg8+mv6vGCAi380iowpMbx35zqm3jCWKdeMRgjRxV3ucLNDMVz07fHnFHD8xS9A84GE+OvO\nwmzx4vUGj9W8HWEWXdVFo8BakEf7wb3Y5gYWspBd2SxSCtA0NLMXoSh425pQYiPwWX1dwiyiQx56\nkIvmd/yVIeOWTCN+6XT/vdKxVSyGgIyEYKsAGFob+eIH75I1P41p35qCEJ5OuQA6wyx2Q3cGS+GW\nBl78yT4mnx3DN++fQLjVz1LRh99CyUXRvjZe+GsN0gcPv5VFYqoRCK6SrKfTdQ2z+B93ty7MYhZG\n3E4fL/2+lO2fNnLj7/NIm54I+Mdt9AW9HxV/SGf3vw6w57VCLrh/DlGT0juv3Zdc1H+yh8aPdpD7\nwI0YIwTgwaXb7w0woDSvPsyiU5Ra8HvZFkxDTYmmYdU7KCYTWmsb7rZ6lOThqUvUgSEW2noGeBB4\nrof9x4B5UsomIcQi4HFglhBCAR4CzgYqgC1CiDellAd7u9ipZZlbu1vmismIKTsd1+GiIfWdtuIM\nrFlxHHpg7aAs59SJMaz853xKNtfw/He20d7UPeSRmm/j/16dTGKWhZ8u3cPuDc0heho8CmbYePC9\nUYRHG/je+YfY+tHgLJX8+cnc8MKZHFlTytqfb8Ld33J5JyFmdp5/fkNVMKbEEDGn74mxDlinjKNt\nx/4e9wshUGOikB6/stEam1EHyAn3NjTTtr+YhG8sHRSjydXYzqe3v0fqvKyAIu+7D6/bR/mBZv54\n6SaeuHUX1947iqt/OgqTpW+loWmSVY/UcM8Npcw7P4J7n0gLKPLBo/SAg19cupeWBg+/eHMKo2f2\nbI17XRpv/3QbB94p5qKHziR1av9LWTTuLqfk8U8Y/csrMEYPfSUgJcyKdfI4pNNN/HdvJO2PP8Uy\nKmvI/Z4MTSr9+gsFKeUGoEdXWUr5lZSyKfDvV0AHhWomcERKWSKl9AAvARf1NdZTS5lbzMj27mXW\nLGNG0X5g8KEW8C/SkHHTWbRXNFL8jy8H1Yc9zsLyx08nNiOMvy/7korDLd2OMZoUrrorg1sfGMWT\n95by7K/L8biGbzUai1Xh5p+lcudfMnn2N8d56EfFtDYNPHsxKtXG5U+fjSXKxOpvfYaraeBxdGtW\nPPYp2Yy67xpUq5n6tzb2/9yJo3EePIbP5e7xGJ+jTedmN6MOMMzS9M56TKnxGBMGVk0ToH53BRtu\nfZXUMzKYcMu0XhV58eZqnrhhE7+d/wm/mLaGP166hROFDm5/YRoTzuwf26SqzMXdVxezfX0rD76R\nzVkXRw6JUuv1+lj11wp+f8NBLvhGMt/+cy5hET076s3VTl64cT2ax8flT51NRHL/Sd2O4lpKXviK\nUT9eQlhW/KDHfDK0phaQPtTooZdl7gk+RL/+hgE3A+8HtlMBPe+2nKCi7xGnVpjFZkZ62xFmvzsn\nAkkI1kk51D/7FopZ6wynAKhqcNsYCK+Y9GsxGk5iKJhhzu8Xs/7W14hOCyPl4iBlyqbqGAwBZoJd\n506HdySCGOCan2azfZqNh6/fxop7c5h5fhxhSvBYi/Awe46Raa9n8qefVPKLZQe4929JpGUHaqZ0\nhln67yF0qcEhDcydpTD+vUxWPVbHPZcc4K6HMhlV4KfIOUOFWXTbHddVrBYuuGssHz2wlw9ufZ9L\nHj4TW5y1M+SjhAitQNdkowm/vtT/nROXcOj7zxA7MwNLelAuPR2utY7BoHkVFLMZc04q7qOHCJs2\nDqlLGuq8LaqCNHjAbEBrbsKQYEeYtU65gKCMnCwX3qZWWtfvIO9v38Jo9vQuF/jZKu1VLRz/9Cjb\n3t5HS2kTttRw5nx7AkK4u7BVTpaLMMVF8bZ6AqvZoRoEP3xmLGMKVMKU4KR4J8tJV8TdiJcPXmvh\n0d/Wcu23Irnq5ohAjZb+vaA75MLR6qOs0EdpoZu9O1x8sKoRk0XwwOo8kjPNQDtOGUicO0kuinY1\n8+R39zLr6kzm35xDqy94/S4yEEIuXNXN7L37dcZ+cxYxs5MBZ9c6PzpZcXv86sijW7LvZLnogPQJ\nvJVlmDJTUDqql34NBWB7sroPbWrk8ObhidELIRYAK4HTh9LPKaXMFYsZn7O7hWjKScXb3Iq3sQU1\nbmhpYOboMGbdv4Qvbn+d6GQzyacNLu196uIEMrINPHjbIYr3OVjxw8RuE1sRUSq/eCSVt19o5DuX\nl/Ode+I479Lhi/lZwxSuvyOejFwzv7ihiBU/SuK8KwfGOxZCcM6d4xGPFPLKTZ9w6SPzURMGXsvc\nnBRF6jfOofRv75H56xtQTX2HByLOPQ16WYtTqKo/wQhQ7DbUyP677w1vfUnE6eMxxvZvsvLoP3dw\n4LGNCIOCz60hVMHcXy7ol3WcNyuOgjNj2PupP+cgd0o4Y2b0bU02NXh58J5Kyoo8/OmFVMaM67gX\nA9Nah/e5WHlBBVabQPOC2yWxhSv884tR0Edd+k1vnOD1+wu59r7RZJ85sGfB1eRk453vkn3FRNLO\nG03bMJdmd5dUYMr8etL4O9DT5GbuaTHknhZ8lt79e+mg+g9Mej4OLJJSdoRkjgMZusPSAm294pRS\n5qakCBTFi9Hilwq9BWYbnY5n30HCz53U2WbUTXaaAuVFLUYPnqZ2mnaVEXdWdud+fXU7+ygrZ/zm\nbDbcvZYLHz6H2Lxo7LoKiPaAFW5Xnexec4LEUXbS8oO3ssMKTxqv8IfX8/jT94u5/+Ym7v5rKuFR\nKpaA5d1hgV17vZXTZ8Vx93fq2LmhhZ/9OhKbXRmCZe4NfPof/osuMjFmXBo/v7WSwu0tfPPeZCxW\n5aQJVp3lSscq7cG2hd/JITISXrv5Yy59dD4xmeEhKzn6z+tusauKj7BF+Ti2Hqb1w80kXeqf2Ozw\nnjy6pci0AMvBNG9MoDa3t4tl3jGlIVSBavRgsHhxHSrCHGdGsXi7yEXn9XVemmhroenj7eT/9Was\ngclOi65cgzVE7fG8hRkce3kHznr/ZJ853ETWxHDCjUFZ6IB+O1xxsu6lCkr3NBOTZKKxxs0tP08m\nXPH3Y+visQXl4sBuF/f9qJYzzrLwu78mYLZIjMIvgwOViykFMHGKkT07PUgJJjP85uF4EuwenPrS\n7TI48a55JW88XsXHrzVwzwtjSM0No83XFrin+vyC7rkGivDhdXr55K6PSZubxuTrxgGuzt9CLx96\ny1wN8VuFkgvw1/L3lFVgn1XQqQ++jqUZhmENUAGh4zBCiAzgNeA6KWWhbtcWIFcIkQlUAlcBV/d1\noVMqZo6UaA2hJw1tU/NwbD/Sr258Ho2jf1tLS2HP9LuEyUnM/eEMPvj+p7RU9UxZ9Lolj67cyrEd\noccVEWPgZ0+PInu0me9eXMSxAyGWVgHyxph4/p1EzBbB1RfWcGBvz7HiwSAz18Qjb6TjcUvuuKyY\n40UD73/WtTmceetoVt38KdWHBu5iCiHIWDGbylUb8baGvg8DgqogNQ2f24P0+RDm/k0G1r6zlcjZ\nozEl9D/Wakuyk74gC8WogAK5i/pe1cbnk7x2/zE+/sdxfvavAn787BiW/SidrLG9Z4S+s6qFH6ys\n4ht3RHH7T6IwW4amUKqrfPh8IAJPe+4YEzNP77kURGuTl1/ffIx9m1v5xSsFpOb2zR/Xw+f18dH/\nbcCeYmPKbTMHPe76j3bRuutYj/tdxZWYc75+y3wI1MR/Al8C+UKIUiHESiHEN4UQtwQO+RkQAzws\nhNghhNgMIKXUgNuAD4F9wEtSygN9jfWUUuaKzYrPEVoJ2Kbk4thd2GdiCoA5zk7WTfPYd/9H+Lw9\nTz7mLsxi8g0FvHfbx7T3MAE4dUkyy35dwMPf3sfedaFT91WD4Bv/l8iKH8Rz93WlfPpu94lRAKtV\n4ae/i+F7P47gW9fWsepFx7Bx0gHCbAr3/DmRC5ZH84Mri9nycVPfJ52EKZdksOBHU9jw4G4ajg1c\nodsy44ialUflqv5PhvYEoSig+fA5nKh2a79CHtKrUbd2J3EXnzaga5V9XszxL8o476mlxGRHMXpJ\n7ynobqeXF+/cTfHuFu56aTKJmRaSs60svrFn5eNxS/7002qef7SJR15OYv6ioVeOWv+pk6svrGbB\nQiu/+7s/LPCDe2N7vFdlx1zcffkRUkeZuefJUdijBsaWkVKy/neb0dwa838+O1CrfeDwebxUPvcZ\nhvDQLxJvQws+hxNjUnDZv6qHXsVbP7wMMY9U+/UXClLK5VLKFCmlWUqZIaV8Rkr5mJTy8cD+b0gp\nY6WUU6WUU6SUM3XnfiClHC2lzJNS/q4/Yz21wizhRtzOdkymEJMviRbMydF4C4sIn+BfMsyk6jjl\nagdf2O825yzJp/HzvZxYvZX85ZM7K9Z1mcgyuJl5VRbtlU289d11XPf4bExhhk43Olzxf86YH076\nY3n8+duHWP6TdBZe4o/DhgkdN11xsfRiM2PzE3nkN3UU73Pw/bvCUQNxdJMuzLH0fBPjR8fwnVsa\n2b3VxX2/iSDc1v29q+n0vP6V5An859a5wEYZvBdXr7AyeVIiD/yikvoSB5fdFI2q42HrOeWhMG1x\nPAavkw++/ynLnz8bW2xXK0+he5hD/1vlrjyNrd94jsxLJmCN9SsYvbvt1XTutC/AQ5fdwyyKQcGg\neMDlRLVbQstFx4IKAde9accRLHF2YkZFAZ5ucgEnLfGmumkubWLL79az+M8LSBhnp+C1jsxFd5eQ\nWwcs3jb+8f19JGRauf6BPIxmrUs45WS5AKg54eVnt1YRm6Dyr7fjsYf7edh6uTB23EuCCJVfpEnw\neCQP/KGVN99o5++PRDHjNBMeKZiyPp7ETIXOhTZ0crHtUze/urOGlT9MYPGyKMBFm04U+pILKSUf\n/WU/uD1c8sAsTFYN1Ru8L31NnHfsVxUD1Z/sxpYdR9SY2M6x6uWivaiUsPwUzAEyhJQSx6Z9pN56\nPopp+ILz/y3Znf3B1z7SvjKZhBCxQoj3hRA7hRB7hBA39NSXYrPga+vZPQ+fNormLYU97j/puky9\naz6HX9xBa3nPFqoQgjPvmERspp1X7tyK5gltyedNsfN/z41h1QPlvPlUz+GbvHFmfv1gLPt2urn9\nxqz8pnMAACAASURBVDqam0L3lzPKwOq3/YrukiX1FBYO7+zR2Elm7nkolTWvNvLor6rRtIF5AJOW\npDPuwkze+N4GPO0DG5s5LpyUJZMofnZwFNAOmNLjwedDa21HDe9fMau6j/cQf27/K+x52z2su/tj\nZnxrEgnj+175XfP4ePKOA5jMKpfflYPR3PcjtnOzk5svqmDeOVb+8Ggs9vChPZY11RrXX1dPTY3G\n2x/EMeO0IHskPbO7/Sal5PnHm/nNXbX89rHEgCIfONY/cYQj66o5664pmAa47GGX8fgkFa9sIuXK\nnr2ntsPlWPODrCitqQ3FbESxDn3hFT00RL/+/hvwtSpzXSbTQqAAuFoIMeakw24DdkopJwMLgAeE\nECE9BtVmRushzAIQPj2Xpn4qcwBbagRjVkxl++8+Q/p6VmZCCJb+v0koBsGbP92Br4dj0/Ks/Pyl\nsax9uY4XH6jsMUQSHaPy0PPxZGQZuGZpNceOhE7KCQtTeODPkdxwUxiXXVLH22+3hzxusEhIMfLn\nVZkcO+jij98tweUcGN99zq0FRKXb/z975x0eRfX9/9fM9vTeQ03oSBcUUFDAAoooTUEsoCAWRAUE\n7ICIUgRBiqIUAQUEqaKiKE2QJr13kpDeN1tnfn9sNplNdjcb0M9Pnuf75rlPlpk7d+7ce+bMueee\nwqbxe5Ds1bs2sW8b8g5doeRKVrWuU8J6PRfZLmEvLKkyAQKArbCEgoMXCb+7Igm6hyzL/PXJbsLq\nR9Dw0apjtthtEstHH0WyyQye1sBjTBMltqwp5Ju5eYydEsGzLwVVO/lIRezbZ+Hh7tm0bavjk2nB\nhIV574PFLDNpbC4/rjWyYG0ct7WuflhlgB1LL3N43VWeXHAHhpDqWzspkbv3HCq9lqBmNTzWKTmT\ngp+CmVsz8tBE3thHyBtupdgs/7aapcyTCUAQBKcnk9It9TrgFJUCgWxZlt2KerpgLbLRVBbJzmUn\nXZTRN4oiK1QPmRkY4kJdchk6bYcrLqGb9KtP6q9nubz+OA0fq+/WasXx28LT05vwxXMH2DLlOH3H\n1XVx13cul/0TYMZ3iXz2TjozRhkZOyUCtUbAX2E7rBfsoIUJHwSy+jsVz/bJ5JNpwXTt6niRNKVf\nelWpXnPIwADaNtMxeGgO50/ZGTUyCI1GQFIsUe2KD4e19LhyCW11sVZx6inAPwQ+XRzF+69n8+6A\ns7w1O56AWGebVTOWxyY25eMOW/iq47d0Ht2CRt1ruiaf8IRQkcSHG5P+/R4ajLrPVc0iKiwYSq1Y\nlPa+TpWLoBJQizbQCwQkRXmkCwC1yk7azqOEtqlFQIgK59LdE10AXPntIubsYrpN7UygQg3jznLF\nnxIWv30aa6GF1+cnoy1NauGki4qqFVmWWT4/n7VLC5i9KIK69TRl1iwaxbwqcjNUogsAsfSYLMt8\n+XUx02cWMnN6CF3u1ZeOm2e6yMywM+y5PJo207BiTRiiQXaMi3L6lN/o0uMV6WLX6jR2Lr7CsMW3\nExoDRXb3ApevTO/6qj3UfLw1Bo0NtUJwctKFbJcoOZtKaKMohNI5N+bkoIsJRqupes+sOriV0sb9\n2z31xZPpC6CxIAipwGFghKfGVH46VF6WUYJKRB8fSvZO36xaAESVSLvxHTm28hT5V71vnmj0Kp6Z\n04Kz+/L5eeE1j/WCw9S88Ukshfl2Rj2bTnGRZ6m1dz8/FnwdyvixBcyaWeRRmm/WVMvWzVFcvWbn\n0f5ZZGb9c0Sr1Qm8+WkcwWEqBt11ntWfXycvyzcXfrVWRduBtbFbJLZNOcTnndexa8peTHlVW6sk\n9mhC1s5zWPNvbMUhiAJIEkGtk4gdeHeV9TN+OU5U1yY+tW0ptrD/0720GHwbar13mUeSZJa9e5ac\nVDMvzGmMtgrViiTJzPwghy1ri1j0fSR1692cS76xRGL4K7ksW2Hkx/WRZYzcG44fs/Low9l0vFvH\nuHeD8PPz6JLutZ19mzJYP/MyIxY2JTTe97jtnpB7NBVLTjGRHZI81im5mo0m1B91UPnmqCUjr1rW\nSb7if+gBetP4L3x2xgKHZVmOA1oAcwRBcOv9kfXjAYrPppG2bDuFRy67bSzirvpkb/cePrUiQuqE\n0vDRemx7a4dHnbgThiANLy1owv7Nmfy4MM1jPb1B5MP50cQkqHmpXxpZGZ6Zb4uWWtZvDOfUKSsv\nDs/DaHTfh5AQkTmfhnJnWx1dH8zk8JF/znxRFAUmfJlIXC0N30xLZ0iHk7zW+RCL379I2kXvzLbJ\n/Qmo9SrsVgmbyc7JNWfIvVC1pYwu1I/wO+qS9uOxG+20V/WYEiUpuagMGkJb1/Kp/uH5B4htG09s\ni6ozF+1deY20c0ZenNcErcF7jBWLWeLdlzM5e9zC5ytjiY69ucXxhYs2HngoE0GAzesjqOVGJ14R\nmzeaeHpADuPeDuKlkYEeVTsWs8zkEans3+HeNPfgrzms/PA8r3zZlOja3s0XC1KL2TrGuzoT4MoP\nR6g5qJ3XiIrqIAM1hnZ1OVZ04holVzK5vuwPri/7w+s9qoObic3yv8a/rWbxxZOpPTAJQJbl84Ig\nXAQaAPsrNlb72Y5krd1DjcdvR9SqEZUu6KXL9MiWcZz5MB8pMwe/+HICcy6n9Yq8nMocna0fr0Pa\nnmv8Nf8InV52BIRS5mJUulgHxoi8OrceUwYew09n58FBkeiFyioXvcrOO5OD+XJWAU8/msEXS8Oo\nXUeNrnS5q1Usl2vFavj80zBGvZlHz0dyWPZ1OLUSyqenbGmtgvfHhNKiiY7+A3KY/F4I/R7zd1G5\nOJ1+lM4lrlEXS5MBKCWKUnqcNCeKwQ+nYLPKZKVY+HV5Bs3aGoiuXW4mV5bkoHTZm1BPT9mjCNBj\nRkdqtwkFysfEk/RS97EmHHrvR2r2bVn2AistHOxl1izlHzi5dJmvUoFWsKJX29xGbYRyusj56yx+\nsUHotRJ6VWXXfSVdFJ25zpWtF+j93cMYnHk5FfNfkS46PBZF10cCMARIgFTBEajUSko0c+qomRED\n06jfUMPnSx2OQHoFDbujC43yd+kkOVUrv203MXdBIc8ODOT5pwPKzA2VqhUlXQiSnakzClnxXQkr\nVoTTpLEGi+yeLgoLJEY9n0VAiIp2bUV0ohnJqfISBQ5sy2fNjFRGzq9PnYZawFqJLgCskgqbxc7G\nUbupe19N/DTW8oQjuNJF5qFU8k+k0ezNLoilai+TvfK8aqP0GCJqAfYyutCH+xFyexKhbR0SffqK\nHfwTuMmoif9T/NuflDJPJkEQtDg8mdZXqHMS6AIgCEI0UA9HaMhKEAQBdaABW6HnJbyoEoloX5fM\n7b6rWpxtd3mvLUfWXeHy/qo35cJjdby/tC7rvszg5xWe6wuCwHMjghn2cgBP9snm74OepWm9XmDW\njBAe7+NHt4cy+PMvz8GtHunux8ZVkUyams9DfTMwVXPz0hOSGmqJr1WuyurSN5z2D3oPRCWKAokt\nwvEP19Ggazzntvru2hzSMBpdmB9Ze24g6mU1JPOsvReJaFu7ynqSXWLn5D3c/lJL9CG+bQZqtCKG\ngMpykcUscXBHEXPfv06vO64w+KFUdDqB2Usjb8oRSJZl5i0sZNiIbF57OYihzwRWaWNfVGxnyNBc\nfv/DzKaNDkbuCZnpdp7vl0HtJA0fzI5Cp3dlE/t/y2fOm1cZPrkGdW6rOhzCr1OPERitp8WA+l6f\n6cSCvTQa3Mbn2OhKFJ1IQRvpexx5XyHJgk/lv4B/lZl78mSq4AU1GWgtCMJh4BdgtCzLHhNnqgP1\n2Aq9L/uj7k4mo5rMHMAvTE/391qwYfx+SvKrVmFEJeh4f2kSq+ek89NK7w40vfv7MfHjYGZNLeTn\nnzx/jARBYPjzgcyZEcaTz2WxeLnnBA2NGmj5eV0Uhw5bSKiXSp+BmcxfWMihvy1YLDfubPTYkDAE\nAeo2MXDoj3yuX646YmKPia0Y+kMXerzfkrTD2Zz9xXeGXrPXbVz74e9q91MXGeiTD7e9xELBiTRC\nW1ad/efs6hNoDGqSe9x4XkonFk9O4a1nr7J+SS4ZaXZUKpi5LAat9sZfO4tF5uVRuSxZUcwv66Pp\n0K7qD87VFBuP9MsiLk7F2lURREZ6ZpYXL9gY/Fg6XR70Y8yEkDI/CCf2/FrI52OvMu6LOiQ3q9qp\n6fiPV7nwZzo9PvAeWTJ191UsBWYSu95YpidzRgG6yH9DZy76VP4L+NedhmRZ3gLUr3BsvuJ3FvCQ\nL22pVXY0gXowGtGo7C5WC85IfVrRTmzrWE58mIstKw+/6MDS4zaXvwA6N78b3RXBpXtj+GnCQQZ/\n2riMAPVuVC560Uqt2iIfflOT8QMuYtBKdOsVVJZDU+8SfU6maxcd0ZEiLwzOJT1FYviQcklCoyAI\nlSBwf2c/flur57Gn0zl10s7H74WhVru+DGoBakarObYrgdotrrJ1m5ntu8yIIiTEqdmzQ6nvlRS/\nHAxQr0idrnRJvu9hfwoyw3nouWh+XpnLe0+e4+1vGhCV6DA5cy6jnckOAMIjy5lKj0ltWDNiFzWb\nh6CLCCmtW9kaBUBSCdS4tw5X1h/DlppJQGKoi5rEVuqD7s6axZZfjCjZUKvsrqqVCnSReeQSIQ2i\nCQhSATYXZzIlXZTklJDyxyXuGdcafWkdJ10oacVpdQLldKFUwzmPDXo1gn0/55Fdul9Su56GevU0\nrlERFf12qld0QvmzKukiO1tiwJAsIkJV/L4ujsAA90xESSa79hsZ8FwWrwwNZPjzDlWM1cVEpfz3\noUNmhg7J4+U3Anmsvz8guai3DmzNY+bYDN77sib1mmlwqFbKaaAiXaSfL+KXKUcYtKAdwcECRXbH\nuCmtWqyyY3V1ZN4+mg1thU4juWSQUsITXdiKzCBJ6ILVCMI/bc3y35C6fcF/45NSDaiD9NgKvFtK\niGoVNR5qQtr2G0tY0XVkQ6xmO3tWVxmoDICEOjqmLo1n4dRsj676TtzWTMMPP4Sz9Bsj49/J8+qs\nk1xXw/aNsZy/ZOXF0Vnk5rkn1OhINU/290cUwWIBSYJ3x964lKLTiwx8MQy1RuDBAWH0fj6cCYNO\nk3HNt5jmsU3DaNG/Lpvf2e+TGkSlVRFcP4q0X89Ur6MCPknm2XsvEdm2ZpX1ji09RkjdEMJq/zMS\nnqgSCAxWodEKqDUwYMiNqwGOHrfQ6cHrdLhDx3cLozwyciWWrS6k3zOZzP4kjFeGBXmVjLdtM/HK\ni3lM+iiolJG74vefjEwdm8Hkr+Ko16xqqxVzsY1FI47QdWRDYht4H89Lv15CpVERf3etKtt1e6/M\nArSRVauabgT/p2b5l6AR7WgCddgLjagECbXoucTckcilH46hwo5akMqKRlHUor2saITSItrwM8g8\nNKYBP848x9W/s9EItvLzgr30/zZUSGUluZ6KqYuimTMhk80rC9BiRyPIikJZqVNDw6YfIjhxwsbg\n53OxloBGUJUVNY6iEkTCQzT8sDiG0CA1d/VI48J5CY2gRiOoUQliWXnzlVA0GgGd1rExWJDnkOrK\niiAoirMv5f3TYi8rFZ+v56BQeg6OZO6oC5jyTJXGQSPY0IiKItjpODgZyWzjxJrTpeOrGHc3JeGe\nuqT9dhaVYHc7nyqhvGhEOxrRjqgSUOH4rTzvep2drL8uEnNnYvlxN/e3ZhdzbsNZWj7TxCNdlD+f\nslQeCxUSJQVW3h50iXZ365m/JoZ6DTTc313vlS7K5sdl3lSoZJHXxuYxcVwYE8aEo1GpyubdSQvK\nIsgCb3+Yy8Spefy8OpYeXQJQU05fFelixTIjI1/LZ/bsEO7vpq9EF7t/KWLKuGymLoqmaTO1C927\nGwuVbGXLzDMktQmm7WNxLnShEewu4ytarRyad5DbhzdHI8qV58bLO+6kC2tmPvrowDK6UPqX3Cxu\nJaeh/0YvqgFDXAi2kqr12WFNY0GG7KPXb+g+EbX8GTCpAV+9eoz8DN8k0jr1tMxaHsO8GQV8t8Sz\nrhscZoZrlkcS4C/Qo08mGV7sxtVqkWnvRzLqxVA69brGL39UNhWrXUND17v13NlWz+4tccyYm8/4\nD7xL/tXBA09GUq+FP1OGX8RqqXqzVVSL9PigJXsWHKcow1hl/dDGMdhLrBRe9LhdUgmCICBL3vtS\nfCUXjb+OwFre47gfXnKM5Afr4h9ZvQiBbu9ZYGf8U1do1MrAS+PDqN9Ez/KN0RgM3l+33FwJs7ny\nfImiwNa1MfR9pOp47YVFEo89c509+03s3pxAo/qe/TIkSWbS5ALmzC1iw5oIWraqXHfdqmImjs3l\n86URNGjqm2fn5s8ucuVYIY+N9Wwr7sSJ1aeJbhZF3O2xPrXtDqaMQvRR/2zuTyf+z53/X4SoUWHJ\n9K7KAMeLXqtHAy5t9JoD1SuadIqgQ/94Fo445hMDA6hZV8vC7yJZsqCQhfO9M3StVmDezDDuvVvP\nfY9d59QZ7x+pwU8E892CWJ56OZ05X+VVcuhYviCajctjqJ+s5fcNsRw+YmHgkCyKiv8ZS5eBo2IJ\nCVezcOx5n6I5htUMpGmvuuz49HCVdQVRILZzXVJ/8z39X97RFLJ2ew6RCpDzdwqByZFel+DGLCNn\nN5+n2VO+5yj1BLNJYt7EdJKb6hn2drTPS/+UFDs9Hsli8xb3KsSK+yXucPmqledeTycqQsWW7+KI\nCPe80Wk2yzz3cg67/jSzaX0EdepU3j5bvLCYeTMK+PK7SOo38i3mya61mezfmM5zs5ui0Xm3SinK\nKOHQV0dp/lSTm1KRmNML0UX985YsADZJ5VP5L+CWYuaiIKMP02PLM6IWJURBLi+UFsWx2g8mk7L9\nInajWXFcKisqQS4rzvMqyosoyNw/rAZBEVqWT7hYtndddg3lRXldYk0VX6+OZOVyI3M+LUSWZVQI\nZUUsLeD46IwfFcy414K5v/d1ftteUraEVv5z4q47DOzamMjHs3No2vEqKSl2RBz1DToVWrWDsMJC\nVaxZHkl0lIrBw7PJzJDK7uvsR8WxrTgGLs8nyGhU8Oq0GmReNbF25hW316gqzEG7wQ1IPZRF+t/X\nFWMvuy2J9yaR+ts5BFmqNJ/KpbUoyBSdTkMyWcnacQZBliqdd5a8o6mENYnxeE9RkDmx5DD1utch\nIFLvM12U0105TQiyxGdvXMZmlnnpvWhUAm6vUUKFwIWzNh7rlc2TT/jxWE/PKwNvdLHrrxLu7HGV\nO1vrWTA1Gr1WVUYXzuJETq6dXk9kYrHIrP0ukqhwtQtdyLLMrOmFLF9SzKLVEdRJUnulC2c5sy+P\nb6dc4oV5TQmO0HgcN2f9HTMO0fDRJMJqB3qli0rveAW6sGQV4B8X5HGMbwb/5wH6L0Ib7IfFR/dv\nfZgfUS3iuPpr5eBbp9ad49KfVatgRFFg0EcNOL2/gG3fZvjcz5hYFctWh/PjRhPTphRWKcn26RnA\n0vlRPPtyJl8s9R5WoHYNDbs2JXIl1Uat1pdIaHaBQS+ms2RlATm5CksNrcCMj0Jp1VzLgz0zOXvO\nNxd9b9DpRUbOrceeDdn8+b1nD1gnNAY1d428jV2f7KsyGFdIwygkm53Cc1Xb+Z//YicA9hIrGds9\nb5zmHksjtKnnGOLGjGIubDlH839AKl/0URoFuTZe/zjG54BZBw9a6NM3hzGjAxk+9MakyyUrC3js\n2TS+nB7NK8+Fek8ufcXKfY9k0OI2DYvnh2MwuNaVJJlJ7xWw9ScTy1aHExvvm8Fb6kUzc0ac44Vp\nScQmVW2yeHlvOmmHs2k52PcIlp5QkpKHIfrfkcztsuBT+S/glmPmmlADltyqdbBO1H6oARc2VFa1\nGML1/Db5IDZL1Zsl+gA1Iz6vx5ZFaZz6y/fg9xGRKpauCufqJRvjx+dXqb/ueIeerWtj+XR+Hm+8\nm+W1fkKshh8WxaJRQ1qGnRVrihjyaiaLvnXtnyAIjB4ZzGsjAunZO4t9+33T/3tDULiG17+oz7oZ\nFzj1Z26V9et3S0QboOHkWu8qFEEQiLsnicy/3IdqcKLwfCb5JxwfEsli59y8HchuPhTm7GJsRWYC\nanh2ejq78QwN+jTCL/zm4opsXJzJwd8LGDu3VpWxWZzYvs3EU0/nMnVqML17V19XL0ky4yZlMWF6\nDr9+H88D93pnonv2mej2aBovDQ1k0ruhlT44NpvMa6/nc+yolW9WhhPhxR5diYJcGxOHXODREQk0\naV+1JZDdaufXyQfpPLoFmiri3viCkrQC9DH/vI053NwGqCAICwVBSBcE4Yin9gVBmCUIwtnSEOAt\nFMcvCYJwWJmBqCrccsxcG+KHJc/3wEwxbRPRBevJPuUq7dXskEBYnSAOLPEtjktsbQNPvlOT2SPO\ncum07/cPDRWZ9EkI5y/Yef75XEpKvDP0pDoadmyI5/BxM48+m+ZV331vRz/iFbE9GtXX8Mpz7sOA\nDujvz6zpoQx8JoefvDgt+YrYOgYGT2/ElnmXybrmfTwEQaD9qDbsn38YU573j0lM+5qkVmGimLr5\nGJLVDqKAoBYxZxRScDq9Ur3co6mENIn1mO3GarRycsUJkh6u5/V+VeHA1hzWzM/g7YW1CQj2jTlt\nWFvCmNfy+eqrUJ8CY1XEoWMmEltcYNMvRfy5KZHG9b1vTq5YU0i/ZzP47OMInnqi8kZqsVHixZcc\nG+ZffRNGULBvrMFcIrHoo1TadAmic78on67Zv+QMoTUCqNvp5lO+2U1WbMVmdOE3n5XJHW7SNPFr\nHOG/3UIQhAeAurIsJwNDgbnKWwOdKmYg8oZbkJkbsOYafU6nJqpFIlvEcnxZ5WBOnUc1Z//SMxSk\nes7xqUSTO0MYML4mE569SEaK70GuAgJFli4JQ68XePyJbHJzvasbwkJVbFoeR1SEirt6XuXKNffq\nEUEQGP9qGGo1RISLpGfYWfyd583hLvfoWbE0nLHj8lmy1Ldn9obk20Npdm8EX75yHKvZ+wonPDmU\npPtqc3yV949nWKMYStKLMGV77l/S0I60XzGE8La1qfdyZzquHUZwo8rWEHnHUglt4tlK4vJPZ4lp\nGUNATNVWIp5w/nARX42/yLh5tYlO9M3aY/nSYlZ9Z2TxijDatPZtYzH1uo35i/N57Jk0Ihqcp3XX\nq1itsHNDDa8bnZIk897HObzzUQ6bV8Vw3z2VVwAZmXZ69s7Cz09g+rQQjxEUK8Jilpj8wkXsNhg0\n2jdrlJwrhZzcfJl7xrT4R+zCsw9cRlCJN5yerircjM5cluWdgLela09gSWndvUBwaUgTcHhRVIs/\n33LMXKXXENQwBlux78y07iONSNubQmGKqwoiOD6AlgOS2TbVd1fyO3pE0HNIJB88c4H8HN8z7Gi1\nAp99FkKLFlp6PJpJSor3a7VagQVTo3imfxBd+15jzwH30u8TjwZyVzsD29fH8/u6eKbOyWPcBzke\nVTQtm2tZ83048+cXs3C+55C7vqLTk/FEJBrYOKVqq6GWg5twdMUpitM9W/mIapGIVglk7fMcDkCl\nVaOLDECl16Dy06IJdq8iyTuW5jBRdQNZljm3+hgN+jSqst+ekJNqYs2sawz5qA5Jt/mmJvlmYRFf\nzi1m4pRg6jXwPfTtZwsKeGVcFuu3GMnNl9CoYdvaBAK9ZCXKybXR66k0ft1hZNfmeBo3qPzhOHvO\nygMPZ9Kti57p04LRaHxjijarzKRXUjH4q3hlSiIqL1EOnbBbJdaNO0jTXrUJjr/xD6gTsixzZvZ2\n7CVWrF7iNd0M/mWnoYohwlMoDxEuA78IgrBPEITnfGnslmLmkixgk0TM2cUYs0pcB9T5lXQz0Co/\nHcm9GnBs6TEXPZddFmg5qCGZZ/M5uzMDSXa1HXVtvzwOQ/eno2h9bzBvD7mG0Sgj4f46JezIyCK8\n9U4gj/fz48FHsjhxyv0HyS5L2GUJWZB5cUgwU9+PoOegNJasdP0YSUho9fDTqjjq1FaTVFfNHxti\nOXDYzONDMigqsivqymUlsZaKNT+EsXlDCe+PL0CSZJdnLXsORVFu9pSNhSwgI/L4xAac3ZPN/g2p\nlcat7BpZRBfiR/1Hkjm66IjXFyO8TU0y/7riMp82SSwrZeMrCsgSbs/bLBLWQjMBydFu6SL9QBrI\nENkytvSYK12U99t1TJzPZzZJfPHKcRrdGUKzzuEVxkcxboprvp5XxPKvi1i6MowapaFq7chlxTk/\n7vDOqBBio8sl8JbNdDSsX/ljIEkyR06V8OGsTOKaXeTiFRtbVsYQHl75Vf/zLzMP987i9VcDeeO1\nQCTB0Z+K71zFMbDaYcrradisMiOm1wSVWIku3I3b9vmn0fpraPZ4fRe6KC9VME0lTcoCV9Ydw5xV\nBCqBtD/O/ysemZ5MEVP3X+fwFwfLyr+A9rIstwQeBF4UBKFDVRfcUszcCV1kIJYsV+nu4ncHSdly\n0uM1Dfo25vKvFzBmuUq4ap2KTqNa8MuUI1hNvkvaA0fFklBXx6SXrmGzVk+6HT4sgPFjA+k9MIud\nf1YtUXTv6s9va+KZMD2HMRO8b4yGh6nYsCKGhvW03P9oJimp7p8pIkLF4hXhnD1jY9SIPKzVfAYl\nDAFqnpjRgk1TTpJ+ropwBgMbc2nrRa/SecTtNcnaf8XtpmZFeFpZFF3KRtSoUPu5l37Pf3+Mur1v\n3L559aSzhMXruf9Z39QLX3xWwJpvi1m4MpL4hOpt+smyzPTPC5BlmeAgAa0Gxo903dQ9d9FCl97X\nCE46z50PpPDOR3kEB4oc+C0OfYWohyUlEoNfzKJHnwxmzwyhfz/fN18lSWbmuDTys2289XkCGh+D\nhl08kMPfay7x0MRWPqtEzq897tGJrOR6PmfnbUe2SWCXSdvocY/xpuBJrRLRMoGGg28vKzeIFEAZ\n/a0sRLgsy2mlfzOBtTiytnnFLcXMrZIKuyyijQikJLPIRRpTh/hzfedFl2M2ubyoQ/2p2TWJBW/G\nngAAIABJREFUI9+ewiqLWGWx7Cub2D6RGrdH8dvMk1gldXmRlUWlKGpsaHj5w3gEUWDhx5mUWFVl\ndS2osKDCKguKgqLI9OxlYM6sUJ4ams3XKwqxyvayYsNRnBK6XZaoV0/Fjk2x/PV3Cff1v8blNJPL\neec1NuwIGonxYwLp1dNAl4czOHDMhFWWFcXRD12AinlLwykokBk5NIcCk1Dab8dz2BHLivuxKD8W\nkRxGt9cas2zEIYqLpLI6zjF2jrk6xI+6PRtwdNERl/lRzpsmMhhtiB85p7PKjikTAVglFVZJhSyI\n2CWhjC6cxSaJ5J/JIiApypUeSktBWjEZh1KJ79ag7P5WRVFKYGXPqqCLHavTOX+ggL4Tm2BDXWks\nlONmkVQsmJ7P5h9KmPttNKGxOq90YZVlrEhlpcBoZdDwTH76zciOLbFsXhVNt85+dOmkxy5LWGUb\nVtmGqJHY97cJY4lMiUlGpxWYNy0CSZSxYWfv30YmTs/hjvtSiKuXwuofSpg5NYQOd+kq0YWyf05a\ntqDCIqmY/l4uVy9YeGtBDdR6T++I4pikpiBXYuWYI9z3Tmt04f4Vxlcx7opiLLBybP5fCH56t3N4\nYdl+ZKsEomOFVng6neLMkjLa+KfwD6hZhNLiDuuBQQCCILQD8mRZThcEwc+ZoEcQBH+gG1BlBpdb\nipk7oY0IwJzpKtmFtapB7qGrSDbP0lz9J5pyZu0ZLEWV1RsdX27C2W2pnNle2SrCE9QagTdnJ3Dp\ntIlJI69XW0LvcKeODWsimDWnkPHv51ZpuhgepmLTihjMFpmk1lcZ+0E2ew+Y3Ia7FQSBV14MZOJ7\nwfR5PJuff3G/AtDrBWZ+EYZ/gMCrT2VQVHjj3qItHkmkZutwdi/wvEICaPDEbVz59QLF1z1L52Ft\napK9z7uJojYsAEHl/sUtOpdBQJJ764rU389Ru1cTj1K7N6Qcz2PT9LM8PasZen/vErYsy3w1LZsd\nPxUx97toIqKrJ5GnZ9jo0ceRRWjjKocDWLOmWlYviq5kVhgXo6LHfX5lSUICAwUe6OKQuHNy7dz7\ncDpTZhRw+KgVSYK7O2rp18d3CxBJkpkzMYvM6zbeX1gTg79vDFOWZTZMOEr9TtHUvct3l/3LG08S\nfUcN9JHudetJwzvR8vMnUAfqSOjXhthHWjgY+z+Mm2HmgiAsB3YD9QRBuCIIwjPK8N+yLG8GLgqC\ncA6YDwwvvTQa2CkIwiFgD7BBluWfq+rrLcnMdREBWLJcl/O6MH/0UYHkn/LMjAPigkjumczJVZWZ\njT5IS/dJbVj37mEKM33fTNHpVbzzRQ1KjBLvvZSGxVw9ZpicpOGnDVEcOW6l/9NZFFTBTDUagd9+\niKN2DTUz5hVwf9/rRCRfol2XNPa6sSF/uIeB5YvDefPNfL78stitWkKjEXj/0whqJ2kY/ng6edm+\nq5sq4v5RjTm3LZXTWz3nSNWF6KnbswEnl3jeeK498HZq9m3l9V7WfCOSxX1fC89lEJAUWem4LMmc\nX32MuLvreG3bHYpzzax8bT+9321IdJ2qGeHS6RlcOm9h+vIEwiKqJy0eP2GlW/dMHn3Yjy9nh3mN\n65JfINH7mXRS0uxMn+CIQTNyWHBZLPKwUBUfvReCM4yNn5/AayN8j2Vis8q8+2oWZ46aePOTaPyD\nfH+WQz9cJfN8Id1e832jWbJJXFh9hLp9m3mso9JpMMSFIJlt1Hq6A0kv3Ys29J83T7wZZi7L8hOy\nLMfJsqyTZbmGLMtfy7I8X5blBYo6L8mynCTLcjNZlg+WHrsoy3LzUrPEprIsf+RLX28pZm6zq7Da\nVajCgjFlFmOxq8uK2a4muFUtrv91DZNdjcmuxmJXlRdJjUVSU7d3E04sP0HOtRLMktqlRDaPpXnv\n2qwe9zcmmwqTrC4vkqa8yKWl9P+SRsf4z2sgITJ+2HWKShxxmk2yqqy4LF1lGYssY5YlzLKEXwis\nWBZGTJxI67vT+ONPI1ZZwizbyopSjWLDzqJ5Eei0UFIiY7HC2fNW/INwXIfdUUrbb9JCzeq1YXyz\n3MjYtwoosTqW0sr+2QUVIydE0K6TH5PeyCAlXXb/zLLyWPn4OMdQ1uvp8kE7tk7+m5wMa9lxS4VS\np38LClIKyU8zYrGryubMVDqXckAgNrW+bH6tpXNvtauwlRZZFrHbhDK6cBazVUXxhSx0teMwl7bn\nbPv63+moDBoMdaJd6EJZKtKFWVJjsqnY/PFJGnRLoH7X+Mp0UWF8vvksm10/FfHihDj0oToXdUJV\ndLFpq5Fe/bIYPz6IIc/7YREcc2qVpUp0cfK8iY49UkiIV7H+20ieezaAb7+O4Omn/DDLNqyyxJ6D\nJqbPLqRjey0aDYSECLRqq8YsS2X3tMhyWT+U/Ss0wuvPZVJUJDNhcU3UgTqf6eLM34XsXHyBnlPa\nIGl1bsfV3fhf/eMy+qhA/JNjK9GFs1jsavIv5aOPD8OGxoUubPb/lJrlf4Zbipk7oY0IrCSZA4S2\nrkXOfu9Lc//oAOr3a8Khz/a6Pd/hufrYTHb2LK5epiKNVmDcZ/H4BagY81w6ppLqSegajcAnHwXT\n7nYN3R/Lol3n63w0PZ+df5oocdNWi9u01C/N6i4I0LK5hsQEz0SckOhg6JmZdt4cmUdRUeU2BUHg\nuddDadDCwOjHr5B9/cYSRsfeFkGjnnX4beI+jxuUuhADgTVDufLD0Ru6B1C6rK7cvik1F3WgAXVg\nZWec9K0nie/WoNobn3uXnKUgzcjdLzWssu76LzP4fW0u7y2tS0i476oVWZb56stiRo/OZ9HXofTs\n6d0r9edfSxg2MpuXng9ixuSwMrPCB7oZ8C+1Ff/u+2L6P5XFJx+GsOrbcJ4a6M+Y0b7F/i7Mlxg5\n6DpBISIfzouulD7OG3KuGln2yiHufbUJkUnV8868tOpvavVpXmW9kivZGGpEVKvt6sJWQZfvqfwX\n8N/oRTWhjQrC6iZ1XFCTeIouZGEt8q4maTigKTmns0n5q3JsEVEt0nNyG/YuOce1o95TwVWEWiMw\nekYc4ZFq3ngmneKi6sVVFgSBL+aFUz9ZzekzNqbMKKDfU1kkNkjh0pXK6oQxIx1L5dGvBpIYr+GB\nRzK5cs2ziiQoSGTW7BAMBoEn+2STcd193QEvR3Jfn2DeeeIcmak3xtDbDm1M4XUjZzZUjovjRN3e\nTbm68Th2043FjHGEwHWzX6BWkfDEHZWO2y02MnacI66L51yU7pBxKpc9i87SY0IrVFXkp9z6zXV+\nXJbFe0vqEhrpu07eapV5a1wBK78tYf26cFq5CUfrhCTJTJmRzyujc5kwPoRnB1bWK9vtMpOn5fPR\ntALWrYzkwfsMCILAhxN9Cx1w7G8z3e9MIamBlremRaL20f4coCTfyuLh++k0tC5Jd8X4fB1Azol0\nTFlFRLevWg1WciUbvxrh1Wq/uriVJPN/PW3cPwmTzRG9TQ4IwlZgwphrQR3okF5UoggqNZFdGpOx\n7xoRdzVwGWQXLy21hqYvt2fXtD10X9ILUa1I0yVK6GOD6TK+FT/NOkvPiS0IjNSjUaaAkxy/RUXK\nLZUzUpsIr34cz1efZPLik9lMmBtFZLQalYsEaS/tkyILveL3O+8EMuT5XEpKwFgic183HdEJYJJd\nPw73dNWyaGEoD9ynxy7LLPiymK4PZfDZ7GDuuFOHcj/W6hwLtcC4j8L4em4hT/fK4OOFMSQ11FIs\nlXsvmmQtDw+Nw6Qy8PYT53lzSUP84zSK847fZqn8mFku/11i14IId73XkU3DfyGsZQJiVLk+02hz\n1BVjIghsHM/FLeeIfLAsLIXLMtnuzAjvJm2cXRax2sUyuiibi4gwQruGYbGV0gWO9HRZu87jXycK\nOSwUY+l3zJ33nqiYC5vJxpZxe+g0qgWGuBDMcvn8A2V0obbbmDPsGCd35/HxltswxOgplsrpQlR+\ndBQilAqZgnyJ0S/moFXDsjXhhAYJmEpXNPYKNJKfL/HKiDzy8mV+3hxBbLS6El1cz7Txwou5RESI\nbNoYQVioiEm2Yy1tyx1dyLLMqXMS238tYd33JVw4bSW5sYah78VRggCSgy4AV1qRXOnCZpFYOuIQ\nde6MpmX/JIrsFegCKFEcMyl+G20azq07TeLjbTGhAxsulikV6cKUbSSoXSJmm4ON/RtM9b/CqH3B\nLSmZC4KALi4MU2plT9nAhrFk/HKiyjZiO9bCL8KPM9+7t7xIvjeBGi3DWT58D+ai6kmOoigweHQk\nd97rx9BeqZw5Vr3gVp3u1hEcLCKKEBQocOGCjQsXK0v5KpXAg/c7JC5BEBj6XACfzQzh/fcK+Wqh\nZ+9OQRB4dngQw8eGMWJgGnv/cB+47P5nYnng2Rg+HHiCzCu+x6NxIjw5lEZPNGHP5J0e08clPNqC\na98fvDFPVFHwKW2cE5lbTxDZpXrREfd8up+IBmE0fNB92rmclBK2zj3PqDv/5NgfubwwpxGRib7H\nWrl2xcao4dkk1dfw+cJQArx4dJ46ZeWB7lnUqKFmzcpwoqMrrxL2/GWm6/2ZtGmt5fPPQgkL9e0V\nf7JPNv0eTOezTwq4cNqKSg1zV8VVSx0lyzKr3z2OLkBDtzeqH4Uy+9A1svdfJbpb1ZulsixTcOAC\nhjrRLscvTVmDNbvqfAe+4laSzG9JZg6giwvF7IaZh3eoR8HRa1jzvEdWFASB1iPv4OjXf2PMdF+3\n4/PJxDcNZeXIfdh8TE6hbH/QiyG8/FY4Iwdd5/dffGeGoijw6isBhIeL7PwjkiHPBtD9kUw2/1R1\nG3d11PHFwhBWrzLx6kv5FHsJ1NXloQAmz49m4utZbFrhXqXUZWAMDw+LZ/qgw6Rf8j1apRMNBzRF\nrVdzaaP7j2ZI80QEjYq8/Zeq3TYC4EOOUQBrfgm2IhPhHX0PqnVtxxWu7k6h/Zi2lc4Z8yzM6/07\nn/TYxS9zL1CUayOpdRBN7vJ92X9kv4mnH82gczcDb7wd4jUBxfr1JTzWN4eRrwbw4YRgtFrXurIs\n8/n8Qp55LodpH4fw5uigMmsWXzDgaT8kO9isjj2Yex70x+BjjBYnts69QPr5Yh79qCViNe4NINsl\nTs3eTv1h7VFpq1YYWDIKkAFtVLk+XpZkrBn5qPyrH7jMY79kwafyX8AtpWaxWFVldrTqmAiKr+Xj\nby1dsosOpqVW+xN0exKpv54hoVfLsmvdDbhfjSiSnmjOrkm76DK9C4IoICoyu6OGu8a0Yf0bu1n4\nyhH6Tm+NRud+yFSCm2W0BLffr+ODWAMfDLvGuYsy/YcEYS+1h9Uo1DRaRRZ0jSDTe6CBnr0N6A0C\nvQcYqNdIxfAX8th70MzrbwSgVgsozdKVLDs8XsM3ayJ4d3wBvR7O4dMvwomrpVwOO56hWNJRt6WO\nad8ZGPfsNXLzBR55LpISHMtoY+lyum3fREx6f6Y/fZRhX7dBn+B4WYrs5S9Nka1cx+uyjEZLvWfb\nsvPVjYTckYwu1I8Sq0I9Y1cT/Ugbrn1/EH1zB6O12RUqFalUTaKYP6cwLosabJLoQhfgmsXdSRf5\nuy4hBvpj1fgj2OyKtty/iKZsI39+tIu7J3XGbvCnyOa6urLrNaj0Gkc4AZuMRi/Stn9NCiVXRqJU\nv5U/FPz6Qz7zJmXwzrRI2nXyo1imLP2Yki4Ei50v5xbx/XclLFoWSuMmGoolpXoPCgokRr2eT0qq\nnR82hBGXoC6ro6QLp0rFouiMVRaxmGV+22YlNFxFfp4dQRR4cGA4xZIOo1yuUnGqV4wKNYvzeX/7\n4iLnDxXQd1Y7LLoAnJGl3dGF0V5+zKlyu7bpOIJeR1D7hphs5fRhsSvVLOX9zjuejqFeAhZl3awC\nzOl52FT/HDP/rySe8AW3rGSujQnDnOre1Tf8nqbk/FalwxQAyf1uw1ps4fg37t2BRbVI98ntOL8z\ng8m3/8jPnxwj60r1JNQGzQzMXxPHj98X8vG4bJ9c5wVBQK9IHNCipZaNmyPIzZXo1zeHlBTvm6t6\nvcAHU0N44ukABj2aye8/e5bq42tr+WhVMn9tzWPGyCtY3djKt+wRR9cX6jL/2f3kXqtexMWQ5Aji\n7m/I6Tk73J6P6NQQGSi5VnVSCiVkSQIfXP4B8nafJqS9bxufsixz+NOdJPdtSlRz9xt4Ko2Ke8a0\ncGSR0ghIdpn6Hau2rJBlmSWfZrJoWiYff1ODdp08b0ZeT7MzqG82hw5YWL0xnMZNKm+onjxp4aHu\n2UREiny/JpzExOrJZ5npdp7vl4GxWGbFtgSefjmEiGg1jVr5Ft9dlmW2zDzLgXWp9PzAsb9UXdiM\nFs4u3EPSC518VusYT1/Dr36CyzFrei7aaM+x628E/6dm+R9AGxeGJc09Mw9sXgtLZgElV7OrbEdU\nq7j9g66c+vY46YfcZ87RGNQ0ezgRWZLZ880FpvXczWeP7yUv3XddeEy8mrmr48hKtzFpbA6Z6dXP\nIB4eLvLh5CC6dNHxUPdsftzs3WpHEAT6DPTns6/C+fjdXOZ87DnBc3C4mveXJmGzyXz0zGmK8ytb\nurTtk0DnIbVYMuRP8lKr90FLerotOUdTyT5wtdI5UavGr3YU2T9VM76Gjy++3Wim8MhlgtpUnWAY\nIOXX8xRcyPHqtFKQVsy613bz0LvNqNMuklotQjAEerdesZglpo+8wv7txcxaU4vaXmKQ795u4vEe\nGXTuomfe12GEhLrqx2VZ5uuvinmify6jRgcw6cNgdLrqMZWjhyw81TOd9p31TPk8HIOfyFMvhfLl\nL3V8YqqyLLP+o9Oc/COLF5a0ITDqxiTiC9/sJ7xNDQLr+275YjxzDb/68S7HLOl5aP5hZm6XRJ/K\nfwG3lprFoi5/f8OjEAx6TBYVgiCULa1tKoekFtSxKWm/nCL2yU4AZQOuXDaVfVFDw2gx7l52vLON\nwMWPoA+rLJUkPVCH4z+nYTXasFslCrKsmDV+FEqVX2BnGim7wr1YQgA/GD+/BqvmZDKgRzpvfxJB\nu7sd97IqrWVKF8cuFjCKnwOHBXFbOz2jX8rl9+0WRr8ThNZQ/rJbSy0/rLLjWFIzDfPWBfDBK9f5\nYFwBA1+PJiRc7WKVUCzpQANDP63P0skpvNPvFM/Ma0VYvKN/TpXKbX3rkWfWs2jwn/SY342AaIeV\nSqGt/EU22iovo81qDXVe7MKxab/T6PMkxFK9qHMZHXBPay6N/Zrw/l2QxPIxdc6RLFVWs0iSiM0q\nuNIFIIgKNYsgU7D3NIaGNbBpA7FZwK6wXqpIF9Z8I3/P3EXziQ9RIhgQbFaX8wAleSbWD9tB0wGN\nSHqoDnV7JGOQjBR5cVbJzbaxYvI1rDaRd76ph1ovUii5tmsVbNjtMss/y2T9t0V8MCuSdndqKQGQ\ny+kiP9vGW6/nkZ0tsXRtJDVrqfHkOKzMHO+kC7NdZPkXBWxcWcjL70fRoWsARXK5+s0o6Mr0M0oa\ncapXCiU9kl3m+/dPkHrGyJMLO0CQpoxGlKoVd3RhVKhGsi8XcWXDcVoueAqj1XFeqVqx2hQWLKVq\nFslqw3QpA7FmDSyWchZmSs1HFRHmcuxm8V/Rh/uC/8Yn5QagDgnAcjUTW4b7jbvgzs0wXUx3ZKTx\nAdHtalDj/vrsfneb21yV8c0jkKwSKq2IqBZp1C0Wg49ZZZRQqUSeHhHOWzNjmDQmi8+n5FY7pgvA\nbc21rP4xkqIimf4PZXH2tHeLm9AINZ8siScoVOTlhy9y4oB7yVoUBfqMrUvHfrHMGfAX145XTpPX\n8ol6NO+bxIZhWyn2sHnsDuF31MWvdgRpK/+sdE4XF44uIYLCfb5lfgIckrkPQ1e09yRB7Rr41OT5\nOduI7VKfkEbupUSr0crv7+6m1j2JNH28QWk3BNRaz4w87byR93sfJyJex/AZSR6db3KzbIx+KoWD\ne0x8vSGWVndUFir+3G7isfszSW6gYen3EdSsVX21yitPprP9FyPTF0XToWv144rbrRLfvnmU7CtG\nBi64A31Q9WPcAEg2O2c+/pFagzugi/C9H+aL19HGhiPqXW3xrek5qKPCbqgvHvt4C6lZbinJ3GZS\nu8Qf09SOp/jUdfyDI8ukMZW6VKqNT8BmkcnYcpSQbm3KpDFl8lXl8kiSBRKe6sDhN1ZzaOEx6j/T\nxuXekkokulkUaoOaLmObs/H1Xax4184D425DVItIiuD8dpzSXuVjABbBSt3b9czZYOCTN9J4vl8G\nb82IIq6Ggzg1gkPFoaqKU/nD25/q2Px9MYP7ZTF0VCgP9Q/EhuPlssjlDMYka0CE/m8kktC8mPeG\nXqH7UOj2dCyCILhIYEV2Pa0HJCNHhPPF8wd5eEJLYtqXL1+LbTrqPd6MPJOWn97cRYcP78UepJDg\nFJKXU9oyldoCxz5/HxenbSK0RIWgEsskL7tdJLBza3J+OoSmebn3n1MiV0rmzmGR7SrsVqESXSgl\nc9lmofjQOcKf7l4msdkVG2lKusjfe5b8E2nUWfAMRRbHMzhfVEkWkGwS+97aSmB0EA2fb0ehzRGP\n23l9WZsKm/gz+3JZMfoIvd6oQ7teMRQDKGynnXQhyzJvDb5Es/YBDB4ZhkotUCCBtnTFZrXIfDUt\nk63ri3hneiRt2hswA1WFAlJK5r//bGLquAx6DAjliRfDS+9R2X/AWHHFVooiux5TkY31U89RWCDT\ne3YHTBo/nJGji22OusWKDc4ia2W6cNLEpQXbEPwMBN7bmmKLgMXqmB930jiA3eb4LcYlEPHKQKwm\ntQtdWNPz8e8Q4aCHfwg3mbvlf4pbVjIH0NWOx3wxxeP5iH6dyV69Hcnim524qBJp9W438k5lcHVL\nZQnxgc+6cN/0ewiK9af3F53Ju1bM92/sw2qqvv4bICRczYSFCbTs4McTd19mzLMp7N9pJCfT9/YE\nQaB77wDmro5j129GXn8qnUwPnp1OtL43hA+/r8+fG7KY/fIZjIXu6zfoEkffWe3Y+eUZjq2p7MnZ\neFAzYu9IYNsrP2Ip8C04mTYiiNofPIngJjONf7vGmM6nYM2sOkk04JOduenkRXRJiaiDvUt+9mIT\nV+ZsoeaIB1HpK0uasixzbNYO7BYbrV+/0yed8qHvL7Fi9GEGTGtOu17e9cGCIPD+4toMeiMGVQUT\nxcvnzIwccI0rF6ws2hxPm/bVSz5tNklMezuLWe9n8sHcWJ4cEVHpHr4g/VwRs/v/CSL0+bQtGv2N\nx0DJ3nWW7B2nqfX6Q9VO+SZo1GjcSOC2jBzUkf+wZH4TaeP+17ilmbm2dgKWC56j8xnqJaCrFUP+\nVt8zgegj/Gk07A5OzNvNxR9d47MoPUW1/hr6z7kDlVZk+bDdlBTcmEu6KAoMejWSAcND2bvNyJvP\npPBo+yt0aXyJN4dl+NxOjToaJn0eTZNWOp7rcYWf1xZ4dcSJStQxbkUTgiM0vP/oUa6dch+ONqFZ\nGA9PaMm+r0/y59xjldps/FRzYm6PZ++ojdiMN+b674So1RDY4TaK/jjgU33B34Cg877EN+4/gb5J\n3SrbSv9+L0Gt6xLYrJbb8+e//Zvsw2m0mXC/Cx24gyzJ/PbpcXZ/fZZhS9pSp41vDCagQjRCSZJZ\n9VUuL/e9Rvd+QUz5IoqQsOox0DPHzTz7UCoFeRJfbq5B09bV+xA4cWBzBvOf3kunwbV5YHxzVJob\nZx2m1FzOf/oT9cb3RB3ke2IMb5DMFlCLiCGB/0h7Tvyfnfm/BbMK5bhp4mpgvpiK3SgglhKXZFMu\noSWCH+1C+tSlBHRujajVuNiq2rWVN8Jskgjxsdz2cR8Ojl5FiV1LQrf6SJoKm5k4XMTvndiB7dMO\n8fWIwzz4TgtCEwPKlrZWWbkpqVB5CA7GrxfLPwB9Xq/B3h0mzh11mBDKskxgpI48yfHyiW5ULkqJ\nwI4IKnj0ZX8a3m1h1qirbP3JzPMfJBIUrnFxu3a63hvVOh5+uwnxG6/z+QvHuPfFJFo9kkCx3bnp\n6Vgiq+P1dP+yOz+P/JWcVBMtxnRCVItlS+i6w+4mf8of7B6zhaaTe2ERyje9nOoVs2JTyqZcRttc\n583Q/nbyv9+KvURAEEVke+kzKibeabotF5qRbUIlupBLK8iyjPHQGaJfH4xVsfS2q8t1E3a7iOnM\nVbJ+OkytmcMxmrSV6CJ7+ymurjpCi1mPU6INRGUp/2g56cI5FzaTjc0f/k3RdSO9F3VDGw75toob\nkVXTRcZVM5+PuYxsl5iyuh6xtXTkyzaQQaWwHvdEF2aTxLKZWWxZlcsL78XRsXsQNjTkSRXUb27o\nQqlaKTSr2TLtNCe2pdNvbgdiGoZQYFOoYeyK36UbnErVSpFVYWdu1SJZbJycsIGo/h0R69TEaKpM\nF3bFO6x8n7GXj2FFurBeyUXU6hBtWrjxCM6V8F/Rh/uCW1oyVwX6I/obsGW6N1EEhypGVzeBgl/2\nVatt/1rhtJvek5Nzd5Hyi+dNOUEUuOuNFjS6P5FFT/7BsU2VTe98xZC349EZhLJ9vfwc2w3FFk9q\n6sfUdcnE1NTxRo+T/PWL94BhrXrE8MyCNuxcdIlVbx7BYqx8T0O4gQfn30dJrontb/yEVZFQWxAE\n6r3aBW2oHyfe34hkuzG1E4CuZhy2nDzMpy9WXbmKDVBrajqIIurYynHNnZAlicyFG4gc1A11QGUp\nsfDENS7N+ZkmEx9BH+Vd6jNmlbBp6Bb8w/U8MrcThhDPpoce+yPLbP02i7GPnqblPcFMXJFEbK3q\ntfP37mKGPXCB69cszPkxibt6BFc7SqQsyxz/I4sP7/6V62cKePG7O4lpGFKtNtzh8tytaOPCiOjR\n+qbbUsKanoEm2vM83ygkSfCpeIIgCPcLgnBKEIQzgiCMcXM+RBCENYIgHBYEYY8gCI18vbYibmlm\nDqBvkITlsmdVC0Bo7y7krtuBZKqeGiCwdjhtp/XkyNTf2T9tp8d6giDQ4rFaPDGvPbsvd8Q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M2vP7mTeRcW8KnHLmLRVaVTLus2HsKN3ez7zP3EOwaYf+9HcC8aZzY1CUSOHye4cye5t9w64exF\nCEG0rQl7Ycm4200XZ8hmeVtxtjXzCR0AJLX1biFEFIhKkvQysAQ4jUMYa2khap6EYAx36Wzc5cNj\nvqJm4J+/lIG/vEjepmsARobgp9v24Z6355WR98mP0f7N7zD42PP4Ljkf17qFaHnJOo7C4vSyfqGN\nUZxiTrdM5T2bybmyg2Pf/wu1j9Sy4nPrya5JaqG6anVGJrvdLlt47spwWzVH4xOPErZtvab0dznH\nxcYv5bH0gyFe+8kRfnDVX1h821zm37oAu9c+4vyj5R0HyL95Hf6NNdT+4GV2fvEJCq5ZgX3FcPBN\nLOXs1K0c4bjFaWDRtqR4KtNdXMK3dDVm9yAdP7yP4o9/CsXhHNK2rFrXCA0s1S0jFNC0AzQhYcaT\nmnl6XBemQbjhOMUX34wahFSKbkwN2h5/jOz1F2NXfEOOstHkIq2ZC9Nk4MWXCW7bQf4X/w6tMJdE\ndHS5MCzafP/+VurvfQYt083S/70dV2kmYVmH1Hd1hLP8LMiFYULL3l7e+M1xYmGD8pW5bPrqGmSn\nnTAQ04efm3XGNpFcpNuRlDZuRHWaHtlB37N7yL1pHe6LVhOXpBEOztHkIi0TkJSLNJSYhBEO0fX7\n31Nw3a3YZS+yRXcbTS703l4kScFs7qKnefpK2Vh4p+RdmQzO9mA+GSP+o8C9kiQpgB1YA3xntINl\n1qwh0tFE/vqkZnWqGOes38SxH38Dz9wFuMomTq4EYC8pwrmkhsjeA/T/+Wn6H38WNdNH3ufuRCmf\negY279x81v3gPbQ+f5TtX36OgvVlVF27AFeNf+KdZxD+YjcXf2UNy+9cwL4Hanng+keYf91cam6r\nRs3xTbi/I8/L3C/fwMDOehp+/Dzqo7so+uhlOMrOjMvrv+QSzN5B2u//JUUf+ihnIoISnKYWRdpP\novkyUd0jaX7B44eJ93ZRcsudk0mBjtB1uu//A0ZfHwVf+ARK7sS0Or0vSMdvtxI+dJKS951H1gXz\ncdnePgenmTA5/Hwrb/y6jshAnFXvncXC6yqxuZJ9nJghDVIYJl3P7af5/ldxzSuh8mu3Yy/MIhY/\ns4HP1ON0PfYIviUrcc+pntQ+oZY63GWz8ZTNwVM6zPPv2v7sGV3LEN4dzJMQQhiSJKWN+Glq4mFJ\nkj6eXC1+IoQ4IknSM8A+kvzKnwghDo12PM3jo2//2JxtzZuBJKs0/fYnVHzk79GKJleGynfxRqKH\naxFxHUwTYZjIvulzYiVJovjSeVRsLKX+sUO89qVn8BV7WPjeRRSvL3lbjVsZpV4u+PxKFtxRw4Hf\nH+aPtz9GyQXlLHxvDbaysYNl0vCvqGTRD++i5dG91H3xN2RcsJDM91yM4p1etjtJksi55gbaf/tL\nOh5+gMIb7kCSp9shp3tANV8WhRffMGKZME26XtxC3mXXIynqhIO5EQzR9ZNfoPh95H3uYymu+ths\nCaEn6Nqync4Ht5G5aQkLv/t+VM/MFRWeCNGAzp5HGnjzdyfIKHKx7sNzmbOxEFmRRlATzxRCCHpe\nP0HdT7eh+p3M/fINKLPKJt5xEjBjMTp/9QsUj5fsiy6f9H6BE4fxVk1u4J8O3ikmlMngrPPMJ3IA\npP7/NvDtiY7l0XJp7u1GSzk6rE6vtM/GP2sh/Yd30vDT75C/6Xoyl65DkiTS1FjJsJpLkr+uwgok\nTUPoCSS7HTMWJ7rnBMr6Yeqa9aGO9nxHVo9Ptp02iaL3rKLg+uX0bK1l5492s+Pet6i+YxHll8/G\n6RjufrtpmU7L6en01B1dMDyNt06hyXVT85nzmPPBlRx5uJZn7n4a3/wCqm5fQebiohF84rRTKzaU\n3VDFs3kDzvVL6X7gRU585vtk3nQJ7vPWICmpbWJjOLVS2poSlUYsK7rufTT95kf0PvUk+RddgyXC\nHYuVYWhqLY3iANWEHQWBLTgsC5rkx5nlh5SMmBr0HnwTRbGTUViNFAJL5oLT5CLe3UX7/T/Fs3gx\nmZuvSDIVoiOfvzXOKrT3GL2/fhItz0/p1z+MrSQX3aajp67bHM1Ban1WlmfoSNEUY/Lk5KL7WB8n\nXmxi7++PUrGhkCu+dT75C7IwhUxQAImJ5SJuMflEU3EXUatTVNcQQjB4oJXjP30VIxwj/85NeFfM\nQpKkkfEFKfOKOZbJLTZscktDiUqYsShtv74PW0Y2BdfcijpCfoYPdapcCMMg1HiUsrU3oIVOMcXN\nFN4dzM8ONLcPU49hxKMottE1Hzm1XBgJOv7yKKH6Wkpu+BDj8c8lWcazeiWh3Xsp+NKnMXr76f75\nA0T2HyTzfdeguM8s57KsKpReNpeSS+fQvbOFEw/sYt+Pd1B9ywJmXzMXZ/b0ckxPB3a/g3kfWsns\n25dS9+Qx9n/zOdzlWeRcvJCc82Yjq2MQ5gHF5yb/Y1fjuWgtPb9+gsHn3yTz9mtwLpicScsKWbNR\ncvuHaf3DL+ndtY2cmg1TPoaZiJOIjx8lYuoxOrY/Q+m1H5rQmRZpOEHbA78ic/NmfGvXAiDGeJv1\nzh76fv8kems72e+7Et+62W8L1TA2GKPu6QYOPXaCSG+UmhtncccDl+MtmPnoSiOq0/bsEVof34st\n00Xu5iVkX1xDXEyvTNyo5wiFaL3/PmwFRRRsvolkaMrkEGytw+7PQXNNbDacLsaiHb4TcU4N5pIk\nY/NlExvoxpU7uvfaOmUXRgLVM7kHnXn1lWRceTmST0P1+yj88j30PfYkHd/6Ge7Vi/FvXj1tzuzw\n9UvkriyhdE0+/cd7aXjiMH+6+WEKlhUw94oKyi8oRXW8PY9EsauUXbeI0qsX0rW9gboH9lD3fy9R\nePViMi9bgZY1NvfYVlZAwT9/mNCbR+n9xR/RCnPJuOFqbEUTm21GXIPTTdGVt9Nw//ewOXz4Zp+e\nuXA8JG3m42/TtftlXEWVuArLx90usH8PXU88Qv7N78VRM3bQjBmNEXjhNQaf3Ipv8/nkffYWZJuG\nJM0M62fUcxomrW+1c+zxY5zc1kr5+kLWfnIxpWsKUM+CuARP9tH06H5anz2Cd0ERFR/aQNbKCiLp\nxGwzdKuRY0fp+sND+FauJWvjJUM01cmi58gbZM07lek8s3jXAXqWYAuYON05GB2d2BxFCAu9Kh2Z\nrwgVkMics5xIfzt2ux8tImGk6LojMrNaH5RDAzTMWKqWKA6yb76BeEs7A08+T9M9/41v8/l4L14L\nvtO7bbSHbp1OW80wCVNGLS+k5jO5zPvwWlpfaeDQY7W88s03KDm/nFlXVFGwonDEi6qMxloYwW0e\n/oilp+5xy3TZOnVOT60jKXaCe/V85i5bRLi+k87Hd9L0sZ/iXTkb3+VrccwtQTqFoZCeRrsW1OD8\n6nwCW1+n479/hGvJIjKvuBzNPvwBTZtXLEkjUSwV5uy2LCqu/jANf/4pDsWHO78cOT58r+kAScli\n20hPp5U4mHETW8AcYXJLy4UeCdC9eyvV19yDZlHgDetgpAu6tz9P/7E9lN7xdzjyizCsOchSpzVM\nCL7xFv1bnsaxcC4F//xZtKxMwMSMjx0gO1W5AHCkGCwDJ3rpfrOB2ocOYffbmXPNHFb8w3k4M1LF\nRQBllNw605ELQzdofbWBpkf3EajvpWDzIpb+8P2QnQzIjhgQTbFgrGyY0eRiTJNbLMX8ae2l94Wn\niNSfoOCqW/DMmg+xYblQLKYVa9sqF3pvD8GmWmYtuwk1kBSId80s5xgc3hyigTGDRMlbfCG5Czdg\n82YRjffT/OIf6XzrL2Stu3ha02BbcQG5H3sf8a5WBh57gZYvfAv/VRvwXrwKbYKSZZOB5rZRvnku\nc66qItITpvG5E+z+wVuEu8NUXVZFxaUV5FTnjJkuYCbhqsyj4jNXkPv+TfT9ZS/t33sE2WUn48q1\nOFYsRrafPjORNBXfpvPxrFjFwDPP0/If38J/3gX4L9iIbJvcTMaVV0rZRbdy4pmfM/e6T+N0Zk/6\nmsd711r2PUv27JXYfdmjui+FYdD6wkNEu1opu/3jqN7RZ3GRuuP0PP4oks1G3kc+hG3u2eE0AwQa\neql7qZaWF06gh+PMvnYeG//rUjLnZqOOFkF1BjBiCTreaKLt5Tq6dzbjKsmk+KoafOvmI9uSQ0P0\nDMk4wjQZfHErsZPNJDq60Ht6EbEoittD+We/iE2enomx/dBL5M5Zh6qdbUfzu5r5WYM7s5hAV8OY\n6zXXMCVN82RQfOFNND75C8K9rRRffitM01RiKykg95N3EG/pIPD8KzR95lt4VszFt3EJriVVyRRh\nZwhntov5t9VQc/sC+uv7aXjmOK9/83XCXWFK1xdTel4JxWuKsHnOvFDAeFA8TnKuW4tn83rCe+oI\n7qyl65dP4163GO9FK9GKTg9+UVwusm64Fu/5G+h/dAtN//VNcm+5FW/ZuPn0h+AvX0jhisup2/JT\n5l/1aVTHxDZgSZLHpBsk4hH6mw9Rff3nRl1vxCI0bvklks1Gxa13g/f0aj7xni66nnuceGsrmddd\niWvZEiRJQsxwHpBgYy8dLx6lc+sx9GCckosqWfHFjWQtyMeuTa9qkxCC2j/W4sh24SvPwFviBVVG\nD8U5+Uo9rS/X0/5GM745ORScP4u5d65GzUvmGY8kZnZYGNz6Kkb/cKCY4vFS+fmvJk2isXF2HAPx\n8AA9DbtZfO2ExXfOHOeQZn5OFafYuPk/icT62L3tXtZe/M8IuyU4IVW30XBYpq32VIh+Ik7j6w8R\n7W2n9Pq7sPmSQpuwKAVpc6DhsASPWAJJhMPyAttNjMEgkZ17CL6yh0RPP97zFuHbuAR7ZQEOW/IF\ntBY0sKmnB4I4LAEhNmX4pU1rYOmAkGDLIO2vN9C6rYnu/R1kzc+haH0ZBevL8ZZnIEnSyOn60HTa\nylSwBIek2nHLSxu1BpKk2tbCAbG2AMGX3yL4ylsoHjee89bgWbwc2ZnUjNJTaEiaViInG1CcTpy+\npB1dtZguRjO5qCnzVtOuJwi217Ng48eRFQ0lnuoL/XQzS3PDK0QjfcyuvvYUZlPquRs6wpl8sFa5\nCMX7qHv2PryFsym88HokWcZSp4OEE3q2PU/v9q1knHchGesuQHgt5oTR5MJuyWRoszzLVKELu2Z9\n/jqh2lb63zhO5EQb4fouss+fR9FFs/EtKMRpGcDHk4tke3SWk5kweWTTz5FSKS+MWAJJlhCGIGdN\nGYUbZ5O3oQrhHVZ+piMXowYFRVOZKk2T6O7D9D79FHpHe3KdplFy84eHInRHkwurGS4tF8nlycRq\nta/9El9GBaVzLhxVLgC2Pv1PM1KcovwX35zUto13/n9nfL4zxTmnmTucmdgdGQz0NeIrmByLQlZt\nlG66g+49W2l9/iE8ZXPJWrIenNPXcBWfB//l6/Bfvo54axfh13fR+q0HUP0ePEvL8S6twlZTMDRd\nPRN4in3MvbmGuTfXkIjodLzVSutrJ6m950ky5+Vg9zvIWVpEztJC3IVnx7OvZmeQccMm/NddTHR3\nHcFX36TvkS24F9fgWb8WV9HIEG5nWUWyMUXNq2TZlTRue4hQfyve7PGdlrKsIstjT4lkRTstMXSw\np4ljL/2c/MUXk1dzAcYY5AlnaRWVS9YgZScHO+MMVTQjEie4u47AjmMEdh5D87vwr55N2fvX45lX\niCRLI6I9zwShtgCdu1qxZziIdCY5mpIs4S7yseZbV2MvHA6Gi06/XOuYSPT1E9y9l/CuPWAKMi+7\nnGj9CQa3vYqjpGzUVAuTRfOh50nEwhTPOm8Gr3hsvMtmOcvIzl9AT8fBSQ/mkGKSLLsQ1+z5dGzb\nQvfOl8m54FL8S1cjyWdmkLYV5eK6/RKyb72I6PEWorsO0/6rv9DY1I1nQTG+pZVkryzBXZU3pClN\nF6pTo/j8corPL8cwJQYb+ujc1Urba43s+8F2FJtC9tIispcV4V9Uiqt46sV8x4Mkyzhr5uGsmYfZ\nGSK44y1CO3efNphP+/iSzKyVt0xqW9M0MYzJ557pazpA59HXKV1/ExkV4zNnXFvZWFwAACAASURB\nVGVVwDSrBKSvLxKj7/m3CO08SrT2JK55JXhXzaHkvetwFCZnh9YZ23QghCDYFqB7bwedu1rp3NVG\nIpIgb3khBWtLOfnscYQQ5C4pZM1/XoWsKcTPxgDe3Ud4+0FCO/eRaO/GtWghWTdci7O4EkmScFVX\nk+jsJnfzqUlTJ4+e5v101r/Bok2fRZbfpqHr3DBcAOfYYG7rjyEUmUL3fI43PovSF0ZJZTI0UuWt\nEpb6gZIlh0Z6Zur2FlC1+S5C7Y20vbmFgT078M1dgnfpsqQDzDrYWrQ2w0p5TBXFMCyc2CQlUsZW\nVY57XgnZt4McCxDa30hwTz21X99DIhDBu7SC8jtW4541Mj2rNXgkPZ1W5Ylzs9jL8igty6Pw2uUI\nIQg19dO9p5X2t1o4fN9bCCHIWlmOozwPz/xCPHPyMVI0meGgINAtbSPVh9ZancJCG0vn1tCcPjIv\nSFbqsQYFjWAjpBkKFg1djQzfi5o2s4RNy3qLySKWHHnk+PAyKUVJUqMJlFhiSC6G+sVmCaZKycXJ\n2tdoPvoi1Ws/hDO/HFLXMNytlqCvUeqJTiQXaZmAYbkw4xLR4214L15J8T++B8WVNElJWoLYJMfw\nU+Ui3h8hcLSd/sOd9B/uoO9wJ5Iikb+2jIy5+VTeshx3RRaSJJEIx2nYcpScVWUs+/qVRCUNEsOs\nGRg2rcCweWUqchGra6X3N38i0dWDa1ENGZsvx10xZyiYbIjNhI2yWz+abI9hckvLhWo1s4RNhDBp\nPvoS3Y27qFn6ATy6GyXVgaPJxYziXWri2YXHnY+i2GhoeJFZsyYf+muFu6Ccils+Qailnv592+n6\n0bM4CkvwLFuBZ+EiFMeZB/KoHif+dfPxr5uPXTWIdQ4wuKcR2TFzQRdWSJKEpywTR2k2JdcsQjck\nIq0D9B9oYeBIF91bjxBu6MZenIVnbhH2OcU45xbjKB2zHsg7HNKEipMQJnVHnqC39xiLL7gbhztr\npmjSE0J2Ocj75I0AKNNwZMb7wwzUdxJu7qdvbwuDR9qJD0TJmJdLRnU+ZVcvYOnnN+LIdY+YfaX9\nJ6rLxoaf3IqnPAtZlTkbiTyVDD/+6y/DMW8WcipBlxQ78wFQCEE81Ed3Yy0NBx5HtblZuurjOJwZ\nZ3zsqWAUHeodi3NqMFd6Qwhb8otfnX0R2+ruo8hdjdeVj+RKDZBi9FsSaW3JYlFRFPDlVeLbVEl8\nc5xg3WH6D++i59knseUX4aiqxFlZib20HNlC+jbT2r8iTl8GGCktTZeGTyZJIGVn4b8kC01NkDjl\n3TbF8AIzpQWaU6BFWbWtdFs3FZSCHLILcvBflLwWM56g71gP4aOtDO5rovPh15E9TpAV7BUF2CsL\nUUuK0YrzsFJ0JMv9paLKR5bxGiUEH4Z54taw7BHaWEojVy1FqtXw8MGUcPIAUmz4oFLKTiCH40gx\nfYRcAMgpymjCiHPo5J8wjDjLV30CVXLCKcWwx5KLofXprIsWsbLet6ym86Fb1PVR5MKwaO6nyoWp\nG8SauzFOJp2hkYYOQie6MGMJPFU5ZC4vI2NlJZUfWIurNBNNHTnCxMZRSB2V+cmPlzlSLtJIWJzk\naYf5CG3c4lQYukdLSgzV5UOdl/TTTFYurMWVTpWLrrodtB94gWioZ6iSlN3uZ/W6e7DFZUgVFx9P\nLmYU7w7mZx92zcOC0qvYe+JBFlXeiMdVcUbHkzUbvvlLcC1bQiIaIdpQR7i1np6nnyLe1oqtqAB7\nVSWOWVWoZXmo2ZnnEAN1GLJNxT2vGPe8YvybU7UgAxFCJ7qI1bcROdxIbMsb6O09qHnZ2MoKsZUV\noRWVYivMR/HOXFWaM0Uq68mo62J6kN3Hf4fbU8Ci6tswzzofeWKY0Tjxth6Mtg7izd3EmruRRILA\nrhPY8jNwV+Xiqsyl8LrluKtyseV6sSkW89OQ2e0cGmGmACEEejREJNBF+h4lSWHZ2k8iqzaYodz6\nU7uoM3vLJ6qBLEnSPwLvJXnDGsnKQzlCiH5JkhqAAZKBBboQYtxw13N2MAfIz1qAJMvsOv47ZhuX\nUVSwckaOqzqceObX4FyaTLRlxuNEOhuJnagncqSW8CN/xgwEUPOy0QpzUQtysZfmoBXloBXmwgww\nWN5OKF4nroWVuBYmnZiJuIIZ14k19KCfbCXe1Ea8sYPuvQdBUbAVFGArLMCeU4itoBBbfgEKf43B\ncvQXLRjp5PDJp8jNmEd51SVJ6ubbdEXCNDG6+9A7ukl09ZLo6EBv7UJv68LoD6IVZmMvycZekoN3\n3Xzc5VmUf/4GZLuGI+UMVZWzoGG+Q5GIhgi0HCPQXEug6Qh2bw4uXwGRYHJALyheid3x9qaPHoEz\n+G5OpgayNcmgJElXA/cIIfpTq03gQiHEpGpSnlujTm8/kiUKUXK7KFAq8JTcQW3ny7S07KC4bB15\nuTUosjYi3H+Ie2wxV1uLV6Sng9bMbCK9TLbhrJyNszJZDMO83cSMx9H7O9Hbuki0dxLaXYv+5Ksk\n2rtxLKjADITRcnyoWV7ULB+OPDdatg8tx4uU50Z2aEgj+MIWqUmNPFbu+ETFKUYUqkg5zUZUlLe0\nzaESeRbTkHU6bcig2LGVlmArLcFNMixbvFdgDAySONmJ3tZOrKGRwTe2E+/qQHG6cZVVobg9OH35\n2LPzsWXloZEM/lEsfGDFGq6fshEoFo5cegoNIAdS3rCQJR4/lpqbRyIIIzZCLrqjJ9nX/xzzcy+m\nyLMQM5J8iMLiwDxTuTBjBomBfuK9PcQGu9C7u9F7u0h0dZPo6UX2uFDzclDysrEV5eCpno2jPBs1\nLxNJltGsPPIU/9w0h5/RO1ouAGExs0jW705q+Yjshqm2ME3ind3EetrR29qJ9rYT6+8mPtiDJ68C\nX/E8Sis34vDmogzG2Pnyd4hFB5hVcvGQbExaLmYSZ6YFDNVABpAkKV0D+cgY298O/N7yv8QUEmaf\nW4P5GPDYslky61a6B45ysmMnTU3bcLtz8eZU4sssx+0tYKbj4WWbDVtpEbbSIgAkW/KpC9NEBPsx\n+gZhoJ9EzwB6b4BAczuJ7kH0ngB6bwBnRS5GIILmd6L6XNgzHag+J5rfiT0j+av57WhuO5rHgc1r\nQ3aof5UiwGlIkoSa4cfmzIR581AjwxV5zI4+Yl3txLs7CLfU07d/O7GeTmRFxZ6Zj8ubhyMjH4c/\nD6+Wg82VMaUMeaNBlhRUhj/uzaFDHB18jaVFN5DlOrMSbYloiPhgL5FoD/H+HuKhHuJ9vej9PSQG\n+1E8XhxlFeCyo+XkYJ9bjpqbg5qbjWQJMErLhTWQ6G8NwjQxA0H07iDGwCCie5DE4ACJwABG/yCy\nzU7w6EFUtxd7dgGujAJ8FQuwZxXgdeQhK8kvqRZK5UVSNBat/jDBwTZstr+yWe/MzCyTqYEMgCRJ\nTpJlM++2nh14TpKkdJ2Hn453sr+JwRxAlmTyMuaTVbKYaHSA3v7j9AeaaD35OqrqxCCB3Z2JlpGF\nzZOF3ZOJlJ2F6nCh2J0Ih31GBkpJllFz/Gg5fjStaGi5zRIBqCoJEoEocjhIYiCCPhBGBELE+0L0\n7WokdLwT37yCpDbTHUQPxkgEY4iEieqxo3rsaB47ituO6rGhOFN/ruSf7LSjOG3gcKB4HPiXzEwB\ngfHu2ZaZjS0zG+YuHKKeCSGge4BoXyd6RzvxYC/9jQdoGOjEiEdweHNxO3NwunPxqFm4XDm4nLmo\nk/RGCEwSIulNPTa4nbbwUVbn3ITHVTzhvgk9QjTSR2hggFiol3C8j3iwl1iwj1iwF1deKYloGC0z\nC5s/G3t+MZ75i7FlZCPlZw45xBPOlAPUEgE60+H+ZxNCCMyYjhmJEw+ZGJE48aCRXKYn0PsiGKEo\nZiiCMRjDDEcwgsn/RSSCkpFJtPY4ssuJ6vOh+Pxobh+q14+juBRtlh/Nl0HhNbeipcJsrVGfcnh0\nO4bTnYPTnQOhv4Kd3IKx2CyRY8eJHqubyVNdA7xqMbEAbBBCtEmSlEtyUD8shHh1rAOcU4N5oqcH\nxRJ+bE13K6VC+2VdxaV4sWUsQCfO3OobMPQoAamfaKiPcKKPWH8Xgy21YLMR7mjAiEUwzQSK3Yni\ndCHbHShOF5LLieLzIwkBTg1JS/7hVJFsNnArSDYbkqoiOyUkVQFFRXVKoCoIJ6AqoMhIjmRecxQZ\nxS6hel3YMuxQBEY0TvdTu2h58C3MhIHQDeZ9fjP27OE86rIkMOMJEqE4idTgHgvEMMJxjHCcRFhP\n/gZi6B1BjHAMPaQjqQq+xeUjsvcNVZS3dq5VAxGnL5NMazvVGKVghLUtIaG6MrC5MtAyh0t6aUET\nQ48SCXYT7+ogHOqkp+swJyPd+DzFLMq3FFyOJKfTIjBcqNsIBADwCSdOCkjEe/A5vJQ5r8QW1Yb2\nOVUu0mitf436o0/hcGZh82Zhd2Viz8zGm1eF3ZOFnJuFYncludophqphYaom5OF7H7pX8/T+Hasv\nrf0+6nMZw0wik2Y5jY/RCqVYlwshEW3tY/8nf44Z05FsKorDhmS3ITtTv3Ybal4GZlwgu53Ibgdq\nfjayy4lkcyG7XMguB6riRvF5kRRlKKWDErGwXSyccWmcQiMwnBnTmiFT1i08cqsDdBy5mFGMMZg7\nZ8/GOXu4BvHAU8+NttlkaiCncRsjTSwIIdpSv12SJP2JpFY//cFckqRPA/dP1gj/TkAw1M7uw78h\nFg+QmTMHtycfj8eLJ7MU3WOxF7qGhS5uS2DGIsSJYEbDGNEIuhHBjOuY8SgGcYSuY0YimP1xzLiO\nMJO/ACIWRSQSkDAQppH8TSQQCQMMA5EwEIaZapsggZQKdBGJ01/PXZ+6H1lTQZaQZBlZkbBlu9EH\no8koUim5HEVKzihS29my3cQHokjp9cCxf/8zpiQPbSf7PBiBCCZycj9JwhRKcr0kIYSM7HVjBqIp\nTqWEZMhD6yUz+auqLsxYFEmSk7bR1Ho5IQ1tqwo7wtBTdDQJJFBjqW0B1YD8omX4Cyz84UD01O4Y\nAzJOkh/3PG380H8rikrXUFS6Npna15Oi41nlwpLH5W8V9nw/y3/3KRKqY0gO05TEuIWaODIPS0pe\nLflY5OjbWAPx3MNkaiAjSZIf2EiS1ZJe5gJkIURQkiQ3cBnwb+OdbDKaeT5JL+wu4OfAM+IdnJ2r\ntWMXR+ofxzQTyLJGW9ObeP0lxOQohhFHl3XMhJ6sUkPy11s8h4xVG5BdXiTnsOafsBA0DOfpCbhM\nS/ItyWITVVJ20nSSJQCbOrxeUw2EKdBEHDNhEG3qoe2h1+l74wTCMJEkiYVfuwHVqSIME2EKJGEi\nDAGGiRAiaac0QJgCTIFpJH8BEgmBMAVGQkqaOoQgkZCS2wqBgYKIGyQSDK03dTnZNgVmIpkQSVJs\nyayEpgBdSraFSDoFhZlaZyY58roAkutFPFWfRwhQnCSioaSGJZKVe5JRewIESLqJy5MH6tSCQTpF\nC/t4HdDYxNRCxNO2etM0EEI6Y9v9uQhJkVFc9hEOzrcDeqAfEVdGZDd9J+NMgoYmUwM5ten1JMdV\nayb9fOBPUtIbrgK/FUKMW6V6wsFcCPFlSZL+heSX4U7g+5IkPZi6sBk1Gk0HcSNCT/QkvaEu2vsP\noZvD/WGaOj1dh5BlBV0xUNSkPVl1OZEVG8JtQ1Zt2DPOrOL8dCDJErKiIttUPPOKqP7q9USae6n/\n8Uv0v1WPuywLxW7RgCZgLYhRsiaOFhACZ66BTTSdtoZrp+2jmsU2qgVNSzv1kQtMLnF2zIxQK95i\nkB5WcRF+KRtDGEjCRJ7ioNzVvo8jzz+EanOiOjxoTg+q3YPi8aA43ahOD0qmH8XuRMryoro9yA4X\n51KO67OFWP1JjJ5+FM2N7HKhuJ2oihvJbme8/ml94RFCJ49RecVdeIvnjLndOwZnyDOfZA3kXwG/\nOmVZPbB0KuealM1cCCEkSWoH2kkWjcoEHpYk6TkhxBemcsKZQtgIcrT7VXqijRS5q3F5c6kpuYaw\nHGIg1EJP31F0I4pm81I178rRp9MWM8tf182ShLMkiwX/70akaCyVbfEdOwF62yGEoC1xgtrom5Qy\ni/ksQ0lFUh5nP0rMwTzHqikdM79oGRmzl5GIh4jIYRKxIHo0RMwMkYgEifa0I4JdRDubSUSCJEIB\nTF1H9XhQ3B4UjxfZ50HLywOHguLzofi8yLkeFL8Xyen4mx32Ex3dhHcfRATCGOEIZjiMGQojEomk\n38npwlFShqQbaL5MVF8mdmcG4dZ6TD3GiSfvI3/5JkqqL/mrMrQmxLnjy56UzfyzwAeAbuA+4PNC\nCD1FiD8GvG2DuZqdDXYbvbEW9vQ+RWXWGmqKrkRTHJjepE0k4bFRTPLlD9CHYcQRijTELR5RXmyU\ntnUZY26bGmSt2vKI5Ezi9EWWbdPtsfjEiis5kMtj8Y1HgVXmZE4//qjntx5gtHuxLLMmkhribE/Q\nl9b2aGXdrG1Ts2j+lqAryekgqgc4qG8lkhhkRc61+EWm9cqZY27gtYFHyFTLyHfOAuewfUykjmU9\nvvX8kqagaX5wD5t5RnzkT3GAmgmdeCKIEQxihALE4wHMaAy9v5tY40mMwQBGYBBjIACGgez3omZ4\nsVXkI6kKaqYPe553KP5AK3ANpR+YSC7SyycjF8H6bpof2Y2W6caW7cGW5UbN9GDLdiP5fEN9PF25\ncK9bhnvdslPKwsmIRAKpN4IZiZAIBTG7+tAH+4l1tRLs2YcRSabkFYZO+46n6Nj1PIVLLyWjeD5e\nWz6yrJwSBzC2XABIpiVC1lrZauxiZFPC31pulizgxjTxPQ0hhJmKWHpbEdR7OTa4ncWZl5GTNXYV\nG0mScLnzxlz/Lt75EELQOniQI10vUOqqYVnWFciSclpwiE12sDRrM7t6nsCr5eDCNcYRzxyyqqF5\nMtEykh8U+2jUxFTbjMUxwwMY/QFEeJBEdz9G7yDBk60kegdJ9ARI9A0i2zW0bB+OkkzUDDeuAh+2\nPB/2Aj+eQg9apmvK2qvmceCdk0e0N0zweCfx3hCx3jDx3hB6XwjZYcO/tIxEzMCW58dekIGSk4kt\nPxOyspE9zmlpzJKqJrOPen3YyEcpHF4XPVpH6GQdsqohTAN7Rh5mPE646yS9dTuJB3rJKl6Ez11E\nTkENDmfm2Cd6u/C3NJgLIb46zrrDM3s5E6Mu8Ba5jgpyHGeXO/0u/rqIxgc42PgEph5jZcmt+BLj\nB49k2AqY5V3N7t4trPV+AGWcohVvF2S7DcWbjZafPSJoyBoBqqk6xmCYePcgoq+feOcAelc/wdpW\nYp2DxDoGMCM69jwvrvIs7FluXCWZuEoycBZn4C7yIWunB8TZcz0UX7tk1AjQuC6TCETQe4ME24LE\n2/uJdwwQONhCvCPZRgjU3AwcCyqRnQ5s5QWohUWo+dlMIShxBDRvBjmrL8ZfOBdXQQWyoo7wpcgD\nUQY7T9DXsJeTx1/A6c6mpGAt+bk1b1/+8lPxtzSYv5MQ9Sn09bexoOJqhGJHWAoqG6msiYbDkvHN\nbglLtqXKZ1lCta0JFoWa1AQTIoGsJY9lzZRnzYSXDiaVLMtkS0IkJdWWrfnILWYKLbVcsaxXJJNE\nOE64sYdIYzeh+m5CjT3kb6ii7IbFY/TIMKxZE4fCvi0h7Jr1pU5RFq3Xp4xm+rAsGxFAm7pvU7WY\nKyx9JZ/Sr3ooQO/xA2TPX5OkMVpmw3LqGUkpB60QgtaWPdQ1PEdp8TqqstchSwpigux4wqZQmrGe\nvuYuDvW9wMKKJMNlJuQiea/Dy0aVC0v/jCYXimKVBWu/g5LpwpbpwqEmUxFbc7NosoER0Yl2DqJ3\nDRBu7ifa0kf/zgZCzX3EukM4cj24ijNwl2bgrcrBWezHOysHm88xqlyoqoSa6cCR6cBZkT+0OprK\nZx7XFYxgBL2zn2jbILH6NkLb9hBreAZjMIhWlI+tpACttBBbfjG20iJkl3OoLxJGjKbv/Bd5t9yB\np3iYi63lZJN30ZVDTnFxSr/LLge+igVk586nyjTo7zxG5/HXqG98gaq5mynwzj9ttiBZsmWOkIt3\nzSzvbHSH6slwl6IqpxffPRNEezvordvFwKFdZKzZQOb6C2f0+KdCCEGsfYDoiVaCte2EG7sJN3Sj\nD4RxlWbhqcjGU5lNzsoS/HPPTVNRIhxksHYfgYN7iHQ24y9bQEbVUlT72Hnio5E+jh58hEQsxPLF\nd+FxFyCHJ18eXpIkFhZdyRv1v6G1Zz9F2eNXEzpXoDg13OXZqJWZsHpk0RJTNwi3Jgf5UHM/4bYB\nmp86ROBEN5rbjrsqB++sHDxVOTgr83CWZMIYlbW6/rwd35q5SDm5KB4niseJWlaCZ80CIJWALRwl\nWt+N3txGvKmd0PZ9GAMBFJ8H5+w5OOfNQW/qJBEI0PbL+yi969M4CieOyD0VsqyQVTCfPN8c+nqO\ncaJ2C73Og8yuvBy77W2kNb5bnOLsYCDajt9ZOPGGk4ARj9J9dCe9B7eTCAfwLVxOyfUfRK2YuuBN\nBDOmE6xtJnykmdCR5K+kyGSuqsRR4Cf/ysX4KjNxFviRFHnoZbW+tOcCjHCI4OH9BPftIdJ2Ek9V\nNTlLzsNbMR9NH7veqhAmrSe3U3/8WUorLqAiP6mNTweqYmNx1Y3sOPorPM5c3GeYo+Vso3vLTvTu\nQdzVpaiLClA9U8s+KWsKnvIsPOVZI5YLUxDpGKT/WC/BE910vlJH4JdvEOsKkLVhDqrHga+mGFd1\nGfZcH/pghNZfvEDHH7ZR/o27sJeMXrBEdjlwzCnHMScVpBVTELpO7EQj0YPH6Xt8C7HGJkAgDIOm\nX3yf8r/7B2xZ0y+Akpk9h+XrPk3TkefZue8+li+6E3cqgdtZxzmkmUvv4PifEZAkSfjcxcytuoIM\nXwUwenmwhNNSpMFlaafekbiWoOfAa3Tu/Au+6uX4Zi/EVTIL053KKGcNFHJYSoGNqMienM6lkygB\nqHZLQQUzSnj/CaKH6wntbyTa1I2rPAd3dTGe6mKyFhVgy/XisAQSWQfuqZSNG7o/a3GKNM98CuXB\n4pZwd11P9WVseJmIW1InRFMlwWISZixG6MABYkfrCO7fi2vOPHzzluKZU42s2YY45yNKgVnKxhnd\nvTTvf5ZoXztzlt+Ky5c/6bJxVpxaNq6jYx91J55l+YZPo2muCeUi4ZROWwbDLJaJ5CItEzC6XIyW\nKRFAP3aSgR11BA41EzraiqPAT+aiIvyLismoKcJTOOwrmAm5SER0+o/3MHiglf7Un2LXULPchI93\nIhIGssvOrG9+AGdl/pTlQm/voPXfv50MGLMga9NmclZsRLbZR8YhjCIXp5aNG15v0tzwCi2N21i6\n5C5czuwx5eK57V9BiDNTqyVJErO/8Z1JbXv8S5874/OdKc4pzbyqZCNed9HEG6bQdWIn3rwKHJ5s\nhBD0Hn+Llt3P4Mwuour6T6AVz4yWD5AYCBLedZTQW4eJHjyBvaqQjHVzKfrIpThnF+J0Dwv9mRbx\n/WtDGAbRI0cJb99F+PBh7JWV+BatIPeq65Mv6ySi8YUQdB95ndadT1NYfSFzFt2EPMnC2s0dbxHX\ng1SVXDjmNvn5ixkYPEntvgdZuPwDTNdpNxGCO3ZhKyxAm50/8cajwJP6wAOoxAgd7yR8qImul49x\n7IdbkTWZ7OVlZC0rIW9VCY7sM9NIVadGxsIiMhYWUXYrRBMKkeY+jvzrn5KpJwAzHOPYZ+/Dt34+\nuXdegZblm/TxzbiOY9YsVL8fNSsLzeElfKyWcH0dx1/dird6CdmLNuDMm94MuKTifEDm6NHHWLzo\nA0P5as4W3rWZnyXkZs4foYGNByEE9W8+hCRJVK65he6m3ciqjbJL34unKFl5/UyHVL2zl/CO/UR2\nHUZv6cC5aBaeNQsp/vS1KF7XCA3szOq8//UhhCBe30xo+y7CO/ahZmfhXbaC7OuuQ/F6RxR0ngix\nQC+Nrz6IocdYcOndOP35yOHJm5QGgk34PSUTbjd71mZ27f0ZJ0+8RHHNpkkffyowevvofGwLsseJ\ne/0K3GuWoeZMjxopqwre+YXkLMyFm5MFuuOtPfTtaaFz2wlqv78Ve46HvFUl5K4qJXtJETbXmb3C\nkiThLMkk1hlI5tLxO9HyM0EIQodOErj7Xhyzi/Cuno9j+UK0vPHpgvayEoo+8Ymh/5WoRMba8wAw\nuwYY3LuDtuceRvNlkn/B1aj2rLEONSaKy9fT076ftra3KM2dWqDYlHEODebnlJll4+b/HBF8Yi0i\nYNjSZpLksmighwNPfAszkXSg2bPymXPzPeAZdp4mLL64VHbOEVNoc4RpZThfeeTIIQLPvY7QY9jK\nCnCvqMazrCyZGAuwpwZxh2bNzTLctiup9YplvYXBkJ5OjwwOOX2wMy2dYY4Szm8N4Y9azCxpk0va\n3AIQtUynY6l2Iq6S6B0k+MpuIsdb0Zvaca9binvlcrS8HKRRQvyBEQN7ut6nGkl+EPr2b6fjlS3k\nLruQvGUXoqZSBqgxS9BU1FrIItUXluIWO1/+LvMW3YzXPzygjyUXYSPA/uf/l6rzbsdfODd5X3aL\n3KTMJ+nnH+vrovfIm2SffymyZpuUXAjTJNZQR/CVnYR3H8I5vwLPBctwL5+PllKk7RZZmK5cKGaC\nvtouOt9spmNHM31Hu8mqzqH0okryVxbjK08GPk1HLmJdQQy3G8WujZCLcFAQ3FvP4Bu1DL5xDDXL\ni2vtYjxra9DyszEsKR9IBRBNJBdSIEbv9pfo3fEKWTVryV1zSTJjaSy93fAhx5KLSFczB1+/j5UX\n/AOalvx4Wl+RrU//04yYWeb8v8mZWY79y7tmlrOGcJ8106RErK+TWF8nds/0HGJGKExw2w6CL72O\n7HPj3bQe33kLkFIDuKyd26YTK0TCILTzKP3P7yZa24h7dQ3+K87HNqssTe4pigAAIABJREFUSQ2L\nTd1kER/opfW5hzCiYWbfcDeO7IJpXZth6ETCPamCIxPD7vQzZ80dHN32OxZu/gx2z/iapWJzEO/v\npf5H/0X+5htx1iyY8BySLOOonoWjehZmJEZ0zz4Gn91O932PknHVarxrFmCfnT2p6x33PIpM1oJ8\nchbmseDO5ehhnZ49LfQc7OTFTz2J5rVRemElxRfOwj87a0pBP/Zczwi/ShqyXcO3ei6+1XOJflQm\nerSJ4J5GWr78IxxzSvFcsgHHwtkj0lFPBNlmJ+eCy/EvW0vP809Rd/93KbjoejKLJ+7rNDz+IrIL\nFtLSsI2KOZdOer+p4l0zyzsAvScPYCZ0JFkhc9Zy8tddjs2XNaGxI9bUhK2wECldfGBgkMCrrxN4\n5VWci6vJ+egd2OcnNUJJO7dNJ6ci2txN33N76HtxP7bCLDwbV5H36duQHbaRGtgUIIRgYO8O+l5/\nCX/1MnJXXYyqT7/qU2iwFZcnb0pBJP682RTVXMzxl39N9eV3k6ybOzpUt5fiG99PqK6W9qcfxr7/\nTXKuvB55knUoZacd78bleDcuR+/qI/zGblq+fj9deT6yNi/Hv2EBaDOjwGkujaINZRRtKKPmIyvo\nOdRJ84sNbPviM0iSRPGFlRRtrCJrQd7MFF5RZJzV5WizZuG/+jyC2/bS94ctCD2Bd9M6PKtWITsn\nz8bRvH5KNt9GqKWepid+jb74fHKXXcRkE5mVzLmIPVv/l7Kqi5CVv9mhbNI4p8wsa2/79pg5PozU\n+2naJPTQIAd+868480opv+pObN4MjBQzbgQrwUJXNxyCRCDAya9/DffypWTffjODr73K4NMv4tm4\nDt/mdSi+JLNATkXzaRYGi2ZG6H16J96Vc/BXJF98hzbMkXaqw22bnNx/5HTaUolIMgm0Bqh7vJai\n1UUULC9AGUVFMEYUHjidzRK3aFpWM0vcTA6mkYSGqRt0v3yU7jcbGdxVT/amRfguWoa9JGfI3AKg\nWxgMZnpgt2joI3N0JK8rMThIz4MPoQ/0U3TNHTjyk85r6zRaiY/8BZCtNULTBQ1SBQvaa18l0tdG\n1eqbR/TFRHJhaNDw3K9Q7C6KL71leP04cmHqcXpe+wuDr20jY/OleM9fj6QoQ+H6AKTasjXC0yIX\ndi2BMEyiu4/QtWU3oaNt5G2qpvCqJbjKs6csFzDS5DaaXCRM6D3aS+OLjTS+cBLVrVK4oojKa+fj\nLfFNSi6G1uvWdsokY5GLeFQheqSBwLPbiRyow3fFRrwb1iWDiBhdLkYzw+mD/bQ88DMcuUWUXHjz\n0OA8kVwcfuYHFM7fSGbJwhFmlu0P/OOMmFnm/tvkzCxHv/qumWXGIYTg5MsP4S2ZR+WNH5/SvgOv\nvgKSRGjPPsKHa7FXllDwT3ej5ecOvbSnwozE6H/6TfqfeB1XdSneVdNP62nEDZpfbuTEY0foPdpL\n1eZKXHlnJ89ItCtIw6MHad+yH3dlDv8/e+8ZJkXR/X9/uifuzOacA7vknIMgUZIgKIoIignMYEDF\nCN5mFANgAhEFEyhJQBBRkkjOOSxp2ZzzTu7nxczs9uzO7A7p9795rvvLVdcO3VXV1dWnT586dULo\n8M4kPjMUUalw0Z9fKcoPHaRg5QoCOnYnaswDKN0s4a8EFUXp+AW7JqIwG8owGkrQB3veFBUEgfg+\nYzi9YhYFR3cS0qpbg9cSVWqCBw3Gt3178lcso3z3XkLuuQt1ivcWVWCXaIO6NyGoexOM2cUUbdjP\n4eeX4BMXTNKoNoTd1MieheoaQRAEQpqGENI0hHaPdqL4XBGpq8/w58RVBKUEk3hbS6J7JboNA3Al\n1/JpnoRP8ySMmaWUrNpI5vSZBIwYiG+PzgheWhGp/ANJGvMU6Wt/5PyKr0gY9jBKrWcHMydCEtpR\ncPEgQbEtr/ZW3MLNVtV/LW4oybzDxI89RudzZlfPO76D4iM7Sbp7Esh2+p0SmE3muyLf1LIIJi69\n8gaS0bkLIxL29P3o2thDEdeWvKwVVZSv30H+6j34tksk9p4e6BLtcdF1Krs44SOTzOXSltYhVjgl\nseJzRZxffYoz684RnBxIizuSSeoTh0bmdt7QBqgVuW2x/SU12lylLkmSyDuYzclfT5C3N52oAU2J\nv70NvgnBVMkksEqHg4/cDt1gqjnvlNJtbja/rOUVFP74G+aMTELvHYNPlJ3xyqUxUSZtOSUv+TGX\n7O61Uo2d37CQiDb90YfVMO6SSyfIPbKFlGGPAe7pwjkVxsJczv3yGfF3PoxPdEKDdGFTO0IXqK1U\n7D1E0ZJV6Hu0I/D2WxC1GrerNK265rlrHL4ETpoAO13YzFZy/z1H/rZU8g9m0mhUa5rd3gS1v6aa\nLgA0sslQOo4r8H5jXE4XRgNc2JzG8eWpFJ8rInlYYxKHN8cvzr6SNDiWMXJp/Urooup0FkU/rkYy\nWQgaPQJtSiJQI6WLJveb5aLJ7kBW+Pd6KjPOk3D3oyhk13JHF9aKcsoyzhCU0t6F8e7/+uolZUEQ\npKbTvJPMT73p/nqCIAwGPqUmOcUMN3X6AJ9g1//lSZLU19u2clx3ydzbAQmC0BnYDtwtSdLyK7mW\n1VhF7vZ1JN31BKJSeVmhiAuWrrQzcoXCnpZNqcSSlQdtXOLKI1ksFP29i4JfNhPQOZnkGfejjQ2p\nfmm9hWSTSNt6gbNrU8k/lkfTYcmMWDAE/1i/6pf2WtlFWY0Wzv91lpM/HkGy2Ei8ozXtX+qLVXtt\npf7KY6coXPgL+vbtCR17N6JaBaaG23kLq9lIadoJEvuMczmu8QvBWFbgVR+a4HCiBt9F+spFJN3/\nDIKXruGCIODbuR0+zVIoWr6azNc+JWT8SPSdUhpu7AaiSkFkn8Yk9k+i+Ew+Z5ccYs2dS0gYlEzL\nMS3wj/PetttbKNQKkgcmETugMaVpJZz57TR/PbqaoGYhNL6jBcHdkq+Jbl2TGEvEK49RufMQ+fN/\nxKdVMwJHDkapaniuBUEkrOcg0pbOJ2fTGqJ71Z9FSunjS1BK+6ses8fxXMUr6AgT/hnQH8jEnrHt\nN0mSTsrqBACfAwMlScoQBCHU27a1cV2ZubcDctR7H1jvTb/F549QmXeJqG5DXY7nH9yKX2Lzy7aU\nqDh6hIodu1BGhBMwtB/alEQUIUFYinIxXcxAnWB3cDCeTSdv3nLUkYHEvTuBgMTLf+Ekq420TWc5\n9t1BlCqBNg+3o/e7/fBRX/v1nKncxOnlJzmx+BhRN8XTfnI3IjpHY3SIodZrtH9rMxgp+uF3DCdT\nCZkwFl3C9ckgU5WXjjY4ss5ml9o3CHN5MZLN5pVVhX+T1hiyL3Fp5UJixz92WZtnCj9fQh+5m6qj\npylcuJKKnXGE3DcUVfjlueHLEdg4lI6v9UcqLObMsuOsm7CG8DbhtBjbirgOIdcleYN/fAAdJ3Wm\nxSOdyfznIoe/2ovwzQGaPdSZgC5Xz9QFQUDfvR0+LVtRun4z2e/NIfzhB1DHNKyiEkSR2OHjOLfw\nU4rD4glsdv2YdYO4OnmqC3DGGT5cEITFwAhAzv/GAsskScoAkCQp/zLauuB6S+beDmgSsBSo1wPA\n5AsIUF6SDmoBs8wZzmI1kH94GwkPTsLiOG6TGS04f8vd8q0qG6V/bqTsn+1EvjIJTWKcTDcuUfjp\nMoxn04maNgHDviOUbDpI+INDCO3X1K4rlJkj+siW0TrHppZOtrmlFQxc+Os8RxYcQq1X0m1SO1J6\nRjheGlO1jTGAUnAup71327bKdJMl+Wb2/3iaw8vOE98jihGf98Uv2Rkbw4TREdBfKdToFkQZ1dYk\nQXAfT8V5VbMAhlMXyf1iKZqmSUS9PRnRR4tkrBm3M0KjXPXhEqFRCca8HCxZOfg1t0eHFGWxtQTH\ntAg2KCtJQxsdb6cDF6hQ+OiplEpQ64NcVXHOqIe1aCFo4GDMa5aRu2k1YcNvd6ELp2oFAOdHVrZn\nolBb8e2YjK7lJEpWbCDjpdlEPdCPoP5tPNKFnBZcf9fQjSZKSfhTbeg1sQkn15xn13v/cLFFEE0H\nxZHcO7om2uYV0oVFcqjfZGoUjagkcGAMzQdEc+bvdA7N3YHw3V5aPNSJyG5xV0wX1QhQEjh6AKq4\nULI/n0vwuNvRt67JhuaOLiQloNMTdc8DZCz8CmVcJNrwKI90UdOZ22FdFa7SNDEGuCT7fzp2nihH\nE0AlCMImwBeYLUnS9162dcH1ZuYNDkgQhGhgpCRJfQVBqHewThgLc/Bv7BoWtmj/v+iTmqAO8S7K\noGSzUfzb7xhOpxL5/GSU4a5LQEtBMcaz6UhmC5nT5qLvkELiJ0+gDPBFELyP5Gez2Li04QynFu1D\nE6il87NdSexuNxUThGtrm16cXsHuRac5sS6dpoPjGP39IPxj7JzPeI0Ff8lsoXDxRsq27CP04RFo\n21xZhELJYiF76Q8EdejRYN3K7Ev4N3Jvi6wOCMFcUoDa37uEBoIoEnrLraTN+5TS6Bj0PS7fk1DU\nqgm/fxD+vVqTO38NZfvPEnV/P3xi64+93hBUPkpa39WYVqNSSNtyge1fHGPHV8e46dFmNO4bfV1S\nkAqiQEL/JOL7JnLmr3SOfL6DEwv2kvxAN0K7xF+1pK7v3g5lSDh5X32P6XwWgcMGNbiK0kbFENZ/\nGLl//kbcuEf5f5J79fpvKSqBDkA/QA/sEARhx5V29P8anwJTZf9v8IkZC3PQBNfEwpCsVirSUono\n532W9qI/1mO8eInwpx9HodFQO9lf2aZdSE49hCRhvJiLqL280Ls5e9I5t/IYxhIDXaf2ILJj1HVh\n4kXpFez79TxHVl6k7agkHlgxGH2I1q0TyLWAMS2XrNnLUAQFEvPeJJSBvlivUDeev3EdyoAgAto3\nbF1SlZ1GxE2D3Z5TBQRjKi28rFh6Ch8dUfc9RMbXX6CICUebkNBwIzfQNoom+f3x5K/cxZlnvyH2\nvp5EDOtg33u5CgiiQJMBcTTuF0vq5ky2zz3Gv1+doOcjTWnaL/qq+/d0zdh+ycT0aUT6prMc+2Ib\nAZsiaDS6PYr4K3P0ckKTEEvUy5PI++oH8hf+RMi40YjU/04FtOlM4Y7NVKSewD/Re6eiawVP1iwV\nF1OpSEttqHkGIM+iE+s4Jkc6kC9JkgEwCIKwFWjrZVsXXG9m7s2AOgGLBfunPxQYIgiCWZKkVbU7\ny9r7BxISxsJcDLZSlL52XXZF6hmsFiPKhEgsLstpmdu147dNJVGx9yDlB/YR+fpTiH5KJKwIKofq\nQWPBajRS+vtmsEkIKiWir5aAjknoNCZErVRtpaJzo1oBEMtKODB7JwWHsuj2fBcSbo7HRzQDdksZ\nH4cJh9xSQSXIExLYjzdktVCSa+bvuWc5tDaL7vcm8MIfN6P1U2G2SUAVZlngKrllS5XDhEMlyqM2\n1o3gKI/OpxDVSDaJ7DUHSP95J1HjbkbXu7NDYjNjltW1yDJVSM5EFnIpzLGcrjqTSunhfcQ+NwWr\nzMXeZTnt6NZSVo7VWIkQG4rFjbSkDA3GUFWI2Re3uUltHuhCERBO6Ni7yF24kMgXJ6EMDHCxI5fT\nhRPyCIg+GvtgfVRW/Md1IrJXEuc/WUvJtuO0eGEA/ol2KV2uTtHLfvvIbtYjXSig4y3BdB3YjZOb\nctn45Ul2zD1B/8eTaX1LGGItpu7JmsXsoAFv6SJwSAwJ/RI4t+oUu59dTsLtrWl8b0eUGle6qPlt\nn9cqmW6iNl0otD6EvzCBop9+I/+HHwl7aHyNhO5MiiLT04gqkeDBQ8j9ey0+zZpV161+HRx/Ky+k\nUnm+QeZ6+fAgmevjU9DH12x+5//7p7tqe4AUQRASgCxgDHBPrTq/AXMEQVAAGqAr8DFwyou2Lrje\nzLzBm5EkqZHztyAI3wKr3TFygLDegzEW5lJ2dD++Kc2rj5cdP4Rvi4az8QAYL16i8JeVREx+BIVf\n3eWwzWgie+bP9us9OAi/rs1QhwdVv7T1QZIkLq09yYm5O0gcnMIdS0ag8rn26cuqysxsWXCBHYvT\n6XBbNFPW9MIn+Nom7KgNU0E5qTPXYqk00XjGfWijgqkyXrlkaK2sJO+HxYSNvhuFry80ML2GrEvo\nk5shCKLbF0wVEk7VhTNXNBZdq5b4ZWeRN28Rkc8+Bport7/WxYfQadZdXFpxkD1PLqHxfR1Ivqvt\nNXnTBEGgeb8IWvYN4+SWPLb9cIF/Fp5nyDONSe5y+QGrvIGoEEm5vTnRN8Wz+8PtbH14Cc1eGEhA\niyuPOCooFQSNvY3cj7+haMXvBI8aXm99fYvWFG3eSNmxQ/i3dr8Zqkt0Za4F/7hlrpePq1CzSJJk\nFQThKeBPaqz5TgiC8Kj9tDRPkqSTgiCsBw5jj8Y3T5Kk4wDu2tZ3vevKzL25mdpNGurTmJ+DOtRV\nxVJ+8ijxvRuOz2ApKSVv7kJCxo5CHRuNVEu1Yi2rIHvWQlQRwTT6fhpqH++ZVXlaEYc+3IzVYKHP\nJ4MJahqKSnkN7fIAs9HK9p8usemb8zS/OYzJS3sQFG13rLiegQVyt53lxMcbibi1LXHjemCwXd2H\nQ5IkCpYsRd+mFbpmnpNyy1GVdh51SJjH86qAIIrzc694TP6D+2FKz6Rg8QqCHx51VTpiQSESf2cH\nQrs34tRHG8jadJZur/UiIOnaJCgWBIHmfcJp1juMI+uzWPLKUaKb+3PrlMaEJXqnaLJZbBRnVKKP\nC/Sqvi5cT+d3h5K5KZVDr68mom8Tkh/uAUrPSUfqvQelkrAn7yP7nS8pDQnGv89NnusKAiGDhpK3\nYil+LdogKK6dg1WD47xKnbkkSX8ATWsdm1vr/zOBmd60rQ/XXWfuzc3Ijj9UX18WPZhMpagTE7Do\nAFGi8kwqyuBghNggLEhISplVguy3hImcb7/Dt28XdN1bAFZElSyjemk+Oe8swr97U8Lv7Y8ggFbt\n6ujhhN6hXvFVmZBsEudXHuPEN3to/WA7mtzZHD+NGajCRyGzWpB5xeiql9M1513ULLWsWSRJYv+6\nXP5ckEFQhJoXFrUiprEeqyQBlYCr1YJzGW2W5MvpmhWCs3+lTR6psW7URoxGDs/ZTu6eS7R7cyhB\nraMBM6JjGSzIKN0gS6Asz3dqdsRQkWTHyvYexJSbQ+SEu7E6riXJ4pXYLLLcoo5hVWVdJODmPlh0\n7l8wMSYUU1F+NV044ZwCOV2YyoooWr6G0AfHIjjUO4LKRsgjoyj4bhnlG7cSMNQetlXlJrmE3CnI\nSRd6lYmqnFK04X74Oc77J/mQ9PkgUledYsvTv9NmXHNa39MMvcwn4WroAqDPMH9uuqUDfy3M5Iux\nu+g2IpwhjyegD3TkPvVAFxlnSvnu4X10G5vIzROSUaoVXtFFwKA4IjvfzZHZ/7L74e9p+eoQglrZ\npXQnPTREF06aEDUawqc8QM67X6KM8kfXspXzQtVtnHShaZOC5mACpRePoW/dupousMlo5XpsVt4Y\nPpXA9YrYfx1hzstFVNdIA8rAIIKH3tpgu5IN/6COjyFgeL8652yVBrI//JnAQZ2JuG+A11KZucLE\nzlf+IP3vVIZ8N4Jmd7dE9DLeuicU5xhY9+UFnJ652ecq+fTBI6ybe4m7X2nEk1+0IKbx9U+ZVXAy\nn40P/orNaKH/d6MdjPzqYc7Ko+jXNYROHGd3KvICktWK4VIa2jjPG5QKPz8kkwmbseHMGIoAfyxF\nRVTs3OtyXNRqCLpzCKVr/6HygEdzXvdjlCSOvPUHxz/8C6uxRuctiAKNRzZjxNcDubAlndWP/UVJ\nenmDfe1blYnV7J0JkkojMuSRWP6ztgNmo403hu7l70UZWEye28c09+fZZd3JPFHK56P+4cK+Qu9u\nFNAEaOn0en/aTunFodfXkL76SJ3xewtVWDBhk8ZT8M0yjBfT662rTUqi/MABr/u+FhAk78p/A244\nZm4tK0PhV2NGqA4LQ5dSv5OKpaSUsg1bCRjUuw6jlmw28ub+irZxLIFDu3s9jsr0YjY/shxNsI6e\nnw7HN/LqzNGcWPn+GX6ffYF/fs5k5Sfn+XDsQdr0Dea15e1p3PHaewXWhmSTOPb9YfZ8tIPmEzrT\n6fX+qPRXtpSuDZvJTN6XPxI4YiDqmLqWEZLNRvaXX2Mtd2V2puwslIGBKHSePVYFQUAVHIy5oGFP\nUEEUCR59O0Wr1mGrrHI5pwwNIuyZceR/vQxTWpaXd2a/focPRmKpMrPl8RVUZJW6nPeP9WP4VwNI\n7B3Lz/dt4PDSVI9Mz1hp5cCaLGaN3snFwyVej8E/RM29/0nhme/acGxrIQteOEnq3mKP9QOjtIyb\n3ZEBk5uy5IX9rH3zAIZS71WDUd0T6DznTi78sp+Tc7YgWW3kbTnJkXGzsRq870fTKI7g8SMoXr4O\nm8nz5om+dWsqT53C5gy58X8BycvyX4D/BtNEr2HV2TBXliKE6rHqbC5GjE6rCWTLaefvkiXr8b25\nI8rYABSy5bJSbaHgl81I5eXEvnI7osrskjhAbq2il/0u3XeOPW9tpP0jbWk2qhlgwlcht1awE5vr\nErqGALUOO3VtreX0pVMVHNuUjyTBkrfO0KF3AB+uaUFwhBpRcGU6UNtqQbacluqqWQxCjRTsXMZr\nrLLofqKa8nwDv7+2B0OljSHv9kAREQzYrysikXcgE7+EQJT+9lgeSg/R+wyy8LSCY2ltUSgp+nE1\n6tgwfG/pVKM/UdrHbbMIVOw9jM1sgDAdVocqQbAKVGZeQNMowf7McS8JSQIowkMwluWilCX99kQX\nmqbR6Dq0oHjteoLvHY5CpnLzbx0FDw8h95PvSZn5IKog3wbpQqc0QwD0fKsfaUv3s+WRZfR6oxfR\nN9n1/HqlEVTQ+8EkOvbxZ8UrB0jbnMaYt5sTEGH3Hq2mC38zU+Y3Y/eaPL558hBdbw1h1DPxOPfr\nXZ2G6krfLZuLtPw2md1/FvHtlGN06BfEmBfi0PvaP8q16aLH4ADa9ejMio8vMP+Ovxg8tRUtBtrN\naDUyaxVVdQ7SmndITNIRMu92dr7+J4ceXUBVVikgYD2eSmC3ZLd0IcjUYBaH961/r5ZU7jlM6cZN\nBA6r2f+Sq9xQ6dA0SqA89Ri+7R0bobIP4vWQkP9bpG5vcONJ5qWuknlDMGXkUHngGP639a1zrnzv\nKUo27CP6hbu9iiAnSRLnFu9n7zub6Pb2LQ5Gfu3w3bRzmGXePflZJgLDrr01jDuc357DwjF/E9Uq\nmDvmDSAg2nWlcXbFMXa+voGKzLIr6r985xEqj6QSNmGkWzWWJEmU/rkF/4G965wznr+IJimxwWuo\nQkOw5HsXowUg8I7BVOw4hOlSdp1z/j1b49+3HRff/QWb0XsnMUEQaDm2JX3e7cO2N7ex95ujSDZX\njhCe7MeEH3oS1zaYT0bt4PD6utcXBIGuw8N59/e2VJZaeXXYIQ5u9ixlu0OXgUHMWNsam01i6tAj\nHNjoWZWi81cxanoL7v2kDTt+OMfKaYcwlHt332p/DcGtIqi8VIzNZMVmspC/7fLNBIPuuZWyP7dj\nyfc8Tn2ndlTsPXjZfV8x/ieZXx9YNRas5eUIEb7YfGwun03BKYEpao6JShvFy38n8Lab0YaoAAtK\nx+aTKTOf3C9WkvjaaPSRWrRKp71wjdTlK7cjF6o4MGcX+QezGPHdEHwjfdHLAnP7yiRvX0d6cblk\nrhdrzmtqSeaSJDH76XOcPVCOKIJSLRAerSK5mQp/KlAqBBe3aidssqWJq2TuSAsnk8A0MslcK9l/\nqwQrFpONtbPOsvf3HO6e0ZbkriGUW+xjFQUbVrONfz46QNqeXG77ZjD+cf5UWAyO83VdvWsfF0UJ\nY3YRBd+uIu71e9EGKbBYaqRcq8U+7sozF7AZqvDp2hSkGsnPZhUwXDiP/2197c8cz5K5MjESc04e\nNp+a9p7oAuw68pDRfSn68Tf837q/+iOjUdvHF3vfTWTk5JD9+SpavTao+rycLnykSipzyglIqgnX\nqlcY8e8SSPQPt7B+6jYKjucy5v1W+PjZ510nmkAJIybF0vMWH75+7hRnNmXxwPR4dH5KlxWbOtTK\nCzOjObjNj69eP8/uVToeez2MoFB7Xw3RhV+QyPPvhXNoh545r5xn3+oc7p8WR0CIvX1tumjfWUPS\nd21Z/u5p5t+zlXs+7UBkYz8kSeLMX5dIuTkSUVmj7nJK3sb0AgSlAFaQrBIF/57B9+XebulCvkFu\nlJ+P9SVwWHeKfl1NxLP2YGo2i0zetAroujan8NeVWKRye8x06fpugP5PMr9OSHvsJaTKKrJe/YDc\nOd82WL/q+DnM6bn4D3T1LrRWGUl/fzGR9/VB37zhxMCS1cbONzdjyK+k/9zbrpl+HKC8xMInk8+z\nd3MpY5+NYMGOFiw/1py5fzVm6icxKK9RVhp3yE+rZPa9+8g5V8mkZT1J7uqa2sxQYmTVpC2UZJQz\nfMHQK4rkZzNbuThjOSF33Yw22fMmaunarfgP6VXHxdtSVIIgiijCQz20rIEyKABT6oXLGp//LZ2x\nVRgo23GszjlBEGj03FAkm8TFRTvdti84msvfj60m92henXO+4Tru/aYXEc0C+XLMDnJS665q4lv4\n8trydqh9FLw24iin97lf+bTr6cfn61IIjVby8n2X2PZHqdt6ntC2u55P1zYlLEbF80NP8O+aQo86\ne5VGwd3/ac4tjyYy/8FdHFiVwV+fnWH5lN2c+jvTbZt+7/Vh+PJ7aP1IJ1T+WsxlRi6sOOK2bn0I\nHHYTprRsKg+59xkQdVq0zZKpPHj8svu+ItxAkvkNxcydsBmNqCLqf7klSaLo178JuntgdZ7O6nNG\nMwH9OxAyuEOD15IkicMfbcZQWEnX13uj1F67xczRHWW8MOwEgWEqFu1pxeinIgkMVV2WjfO/60s5\ntLPisq+9d10+y94+TcdhEUz4og36INdNzvzzZSwZv4HQJoEM/7QWNH+VAAAgAElEQVQXat8r2wTN\nXPAXuqYxBA3t6rGO6VIOpguZ+N5U1yHEePocqphIRC9si5URYZiz6zLV+iCIIuETbyN3wXqs5XX3\nJUSNisQnBpC94TiZv9dlTuEdoujyys1seG4jGbvqMjqFSuTmx5vTe0Ijvn5gF0fW191U1egU3Pdm\nCuNeiWfOpDP8MisTqxs3V62PyENTI5n8TiQLZuQy8/lMKkq99zDQaEXunxrNy9+ksHlZAXOmXKCq\n3HP7LiOjmLCgK79/cIItX58DYO/P5zzW9wnR0WJ8OwaufpjYIc049ulWKjOKvB4fgKhWETL+VgoX\nrUGyuA974T+kd4Pv/zXDDcTMbyg1i6BSIpktCGoVgXf2R9TKltOOpZvCsYSuOnkRwWoiqHczBNGC\nyqFeUassEKnG/+5OaGVOPTo30e30SgP7Z+2i8nwewz4fgFpvBazVG5xy1Yqfi8rF/luuWtHJfitM\nRn74OIetq4t57v1IOvf2RS3UtFcJdd35a6OywsYnbxayf4eB/8wKI1CsrD7nTs3i3AA1G238+G4u\nB7eU8PispiS28gWqUNtqdPXndubx8wuH6ft0S9rdngCYUFplLtaOcYkeVCvOMABZf56gYn8qbT4b\nj0XmQWuSp6NTKMhfu4WAIV1R+wuApVr1AmBMPYtPy0QEjYzpuJkWQQBlpC+S0QS2CkSdfVOxNl0A\nKBQ1v1VKK9rWkRi6N6bwp/UkTB6KVllrszNCQY+Zw/h30nKCojRE96qxxNErTDTtHUFEUA9+f2Er\n/V7pRLuBNc5NTrrod2cIyU1b8/XTxyg5EcKdz8UjKgQXuug/SEv79snMefESb40tYerHUYQn1DxD\nJ1306CTw47oo5rxbxOO3nuO1D0Pp1MN9Vh4Xd34HXXRoo6DFV1F8+WYOb446zAuz42nUwgeDTP3m\nRFV6KVXF5up9xuzjRVBQhH+E/XouNCCji5un9+R0q2COvrSMnp/fgTZUX00XriEAap6Fky4U3VIo\n3xhMxeadBAyuCcDmpAtdq1gkmwBYHX8d+J+a5caB4EgWGzRuGKJP/V6IpZv249e95WVlDa+NI1/v\nJ2dfJn0/GYxaf202IjPOVfHyPefISjPx1e+JdO59+SqboweMjL81E8kGi9ZG06q9dx6ZWReNvHjX\nWYrzzMxY1dzByGsgSRKbFqXzy8tHuG9WewcjvzKUpeZy+outNJ02EqXe8/hMOUWY0vPwv8V91ELD\nifNomzdye642BEFAFRmKOSu/4cq1EPNAH0r3nqXsyEW3533jA+n8zlAOvP0XhSfr9h/TIYyRn/dm\n0/v7OLjCfR8Jrf2ZurQj54+U89GEE5QX1d1gDA5X8c63sdw81I83Hk1nw0r36hQfnciLb4cw9Z0Q\n/vNcPp/8pwCDwfvQmFofkWffi2LM5Aim3X+etT8WuFW7BEdradUnBJVWRKkWsZol/v74qFfXaDKq\nBXFDmrHzhdWYyy/PnDBsXH8KV/yDZL62QekuGzeQZH5DMXNN4wRQiG6X43LYDEYqdh/Hv3fbK75W\n6k/7Sfv7HP1mDUHtf23inuzfXML0MWcYMi6El7+IJyD48hZGFovEgtnFvDAxhydeDOK1D0PR+3r3\nCLf/UcKLd56l/51BPPdZEjo/V7WFxWTjp2mn2f5rFo//0JWkDlfuem4uNXB4+u80ndwHfZJnF3yA\nwuVb0bdLQelX14bcUlSKrawCVVyEm5buoYwKxZx1eaoWAIVeS9xjA0mbvQ6byT0DCW4VSdsX+7Ll\nhT8pd2PVE94siDvn9+OfuSfZudC9ztcvWM3zC1oQ11THG6OOcP5YXRWZKArc8VAwL8yMZtHsQj6Y\nmoOhyj2j7t5Hxw/rosnPtXL/rVmcOX55TLP3bYHM+CWZ9T8X8snk81SWuapd4lv68diXrflob08m\nzO9E4+4hHFuXwe4fz3rVf5P7OxHSJprdL63F6mFe3UGTEIkmNpzyXXX3Mv4vIdi8K/8NuKHULL6d\nm6DwVaHW2QCbi72qc7mnUNgo/ucIuubx+EZqcUZwUiscmc9lbvk+bhIG6JQmLv51lrQ1xxjxVX98\nwwXAgK9MJeNUo/jKVCt+Ys1v59LZqWaRJIl1X2ex8rtC3pgbQ4dOasBYbVcMtd22nUkIau7v0kUL\nLz1ThFYrsGxtGBGRCuQ52VyX0xbHXwUmo8Sc9wrZ9ncVM76NplkbLQbJ4Ojffp3SQgtfPHkRnZ+C\n6UuaI+kAKmtlga9rU+7OxlmySex6bwPRvRJJGZREpcMyRr6crraAyC6mfNcJms17Akkts3BxeNEa\nUs/i0zwBtc7mYt7nbt/Ouc2giQ3GlpeLSmtxjLGGLpxQydzp5XSh75NEyebD5C7ZRsrDdgcyOV0A\nNO4fg7qoBVufXceIBYPwD3FYuDhoISBZyVM/dGb5m8f5t7SC0c/FIQiu6hS90sjEVyJo3lrF3Jcu\ncNejIfS9LQCtQ43ipIsOreHHNeG892oRT468yMwvgkluoqqjfvMLgdlfBvLH6kqeHp/DE8/4MeY+\nHYIgeKSL6vuXrPgnw1crYpjzdiEvjzjOlM+TSGpu/7iKTpt2NbTroqVdl5ZsXF7Amg9OEhEp0GhA\nYnVfnuii2/Nd2D59E2c+3kDHV/u5qGbc0YXzWYUP70DO8l2E9LMna7bKvKudCTjkapbrkc74f2qW\n6wRbpQGFvuGM3cUbDxLYv12D9dy2TS1k78wd3DxjAL4RV+82bzTYmD0lja2/l/LpskRadLz8vJt/\nrq3i7ddLuGWoD1//GOJg5A0jK93CS4/lUlRgZd6aeJq1qZvaLO10FS+NOk3j9r48/XkTfHyvLojR\nkW/2YzFYaPl4w/HJMxdvJ2RoR5R+7p9p5bEL+LRMvKzrq6PDsBS7twgp2rAfa1X9kmvyU/25tOoI\nZec8q2pajWlGUv94tr69E3NVXWkzMFLL3e+04uyuIr5/7bTbzUyAnsODeX5mNAs/ymP++zlYrXXr\n6X1F3vo0mHET/HhodD6//ep5s3vwcB0/LA9l6c8VTHmiiLJS70VGjUbkqTcjeWhqOG8/dI7dGzx7\nnnYeGcOjCzrx23un2L/cvUpJDkEU6DatN6biKs7+csjrMfl3bYI5v4Sqc9574l5z/E/Ncn1gqzRU\nb2x5gimrEGN6Hn6dmlx2/5YqM9te/Zv2k7sS2OjqQ4oWZJl4/Z4z2CSJD5ckEBZ9eXp3s1lixpsl\nzHynlElT/Hhgom+d2NWesGOrgYdHZtKxh5a3Zofh51+XSe/bVML0e88yenIko5+3b8hdDdI2nyf/\naC6d3xyIqHT/UahMK6B4dypVmYUU7zhN2O2erVwsBaX4tE6qe7yknEtTv3DbRh0bhuGM+xgfZXtO\nU/pv/SZtmlBfUiZ05/yPe7FZPDPDzo+1RaVXser57VjNdS1C9EFqHl3QkeIcE3MnH8fkQZ/dqLmW\n2SsTST1qYOoDmZQW1+1LEARG3O3L/CWhfPtlOS8/W0RFhfv+EhKV/LQijMBgkbtuzeP4kcuL3Nlr\niD8vz2vE12+ks+bbXCRJoqLEworZ6dhkq6PoZn489l0nts49zfbvGnYQUqgUtH2uF6d/2E/ZWe/U\nYIJCJGhQR4rW7rmse7imuIGY+Q2lZsFQiTo8ELXadQkNIDqWazmb9xHStyU+elv1EhqozrEpj37o\nkotRYWLHrK1Etgqh7W1xeFKtyH/LVStyaxa9aOT0oQpmPH6BkfcHMfrRYBd3f+dyWiVbjqplLtoq\nQSI7y8rkJ4oJCBBZ83sIIcEitbMhyQW56lj9Non5syv4+ftKZn4RTKduGsCCWqppq7Qp+PnrUrZv\nMfDmvBhadPChUqoZv+IK1pb5JwvZ+/42hs7phy5cgTMRR7WjiONv5pZjnF20G6WfltCejfELUgJm\nl+W2xSpiyi7CeDYD/+RQBNHiktfSZqpAMhqr6QBq1CzKxCDM2YWoMCKqFNV0oVTYCB/YipwVu0gY\nXhML3x1dhI5swr9bTpOxeCcdJ9jj5DstmIBqurj1jQ6sfX4bG17fwfgPW1Z/DKvpwhemzk1m7kvn\n+eih47w6LxHfACU6QaZyEY34hcCsReF8PaOAx0dcZNb8EJo0s3/45XTRrpnIb78H8+brZUyfUsSz\nU/xo1rTuK6zzgfff9WfNqiqeuC+fp5/zY9x4HyyCXXYzyehOJXPQUjmsXdq31TBraTyvPXyJ9DNV\nnNhXScZ5I216+dOkQ433tV8jBU/90JmvJ+xDMBnpNrFFvWa1YoKWjpO6cOydP+g7fxQKjdKtNYxC\nFg4icmhrjj86D+XEPih1NStlm80RBkL6n5rFiRtKMhdUCpQB9aspyvadI7DP5aeXOv9HKnlHcuk5\n9fJzQdbGwW1lzJx8kclvRXD3Y5efXf3fbUZGDiugbz8NXy8IJDDIu8dUXGRj4oPFbNtiZOmaUAcj\nd4XJKPHei/msX1HOlPejaNGhYbVVQyjPrWL9lM30eqkLYc1D6q1rLjOCBJZSA7l/HSd1xmq3VhRl\nB87h2y7JbWo0W6UBhQdrJlGtRBUWgCmzrlt/QJcUjBmFGBqwfRZEgQ6v9uXc0iMUuLFcqb6WUuTO\nmR2pKDCy4u0Tbu9DqRZ5fGYjUlr78MqYsxRku3eRVyoFnn0tkMeeC2DimHz+/L2uzTuATifywUcB\n9O2vYcxdBaxe7b4ewLDbfPhlZQhLfq7khedKKC/3Xu0SEaPi7fmxbF1dTMY5+8fn39/qzmlgpJYn\nvu/M+b1F7FjU8KZoo6Ep+CUEcuyrXV6NQxXki3/nZAo3eWdBc81xA0nmNxQzN2cXIXhYvgOYcosx\n5ZWiT7m8cK3ll4rZ++kuer3dF5Xu6kwQ924o4pNn03jmo3i6D/A+hgzYpeqv5pQx5ekSPpoVwJOT\nvFerHDtqZuSwApKSFCxc4l6vXlRg5fFxuZSV2vhyaRThMVdvbmmusrDymW00v6MxjQY0bMpokZuo\nCQIKvcbtx65s/zn8Oia77cNWZUTUebYw0saHY7hYN1GFoFQQ3KcVeRsa9kzUhfvS5umb+Hf6ZiwG\nz1YYSo2CMbO7kH60lPWz3asbRFHgoVej6TMyiNfGpZJ21rPefujter78PoQ1yyqY82Gpi2pDjrtG\n61j4QzDvv1fOW2+WYvGgl09KUrJ0ZQjh4QruGVnApYveW5TMmZ6D2SghSSDZYPvqArfj0QepGf12\nK3Z9f46j6+pNU4kgCLR/sTcZm8+Ss+tSvXWdCLmlLYV//79h5oIkeVU8theEwYIgnBQE4bQgCFPr\nqddZEASzIAh3yI5dEAThkCAIBwRB2N3QWG8sNYvJhFqvQOOIYOdiYSFKlB1KJahTAjpnQgFZdDen\nI0ht1YrVZGXT9D/p9Egbopv5V8dVAfeqFahZRrtYKIhGtvxWxLfvZvLOt7E0aa1ycRrSyyxXtA7L\nFZVsDWeqtPHaK6UUFthY/3soUVEKFILcUceNhOpo/8vSSn5dXslrL/tx23AfzA5xQb6EPnbKyOMP\nFTF8pA+PPBeAKFqpkGRMRS60OT7xVqn+D4lkk1g6fR8RjfT0eqQJgmBXP8ijOdZGxQW7pKsK0NLu\njSHo2yRRW81iskHFkQukPDMQ0aH+sMr6rDBWofTVoJZFwJQv1/VJwVjTs9GqmlbnpVQ6VG7RQ1tw\n4tWlpDzYFUEheqQLgCaDEyjYfpajX+1m0Eutq8/XpgvfAHj66xbMHHeIoECB2x6uMcd00oBOMHHv\nYwFER8OL96Tx3txwWnXUuqWLzm0UJH3oz1OPFjN5oolZswPw8xNROWjASRdd22rYuDacxyYVcu89\nRXz9RTAR4YpqurDPm4TOR2D6y37ERouMvaOAj+cE0OMmDX+sraKoBO4cY1/tVlvJOKb6uWlB/Par\nhg3LSynKt1BZZmX7r5l0H103BIZfDEyY2565D+3lzlANiZ3remhW00WQih6v9WLHWxvpuzAMTYDr\nPphQy9pF2yGKC+8VIRYXogmzh5SwOqxY5HRha4BerwRXY3YoCIIIfAb0BzKBPYIg/CZJ0kk39d4H\n1tfqwgb0kSTJKzfaG0oytxlMKHw8u5UX7ztHYMe6G2b14cTiowSlBNP8Tq+zM7nF+p8LWPRBFm9+\nn0yT1vVv0gLk5lirl+WZGVbuGFmIWi0wf0EQUVGeVx9l5TbKyuwUZjZLvDathI8+KeM/0/y5bbh7\nlcnGvww8MKaQZ17w45kX/LyW9hvC5i9OUZZbxfA32nqlSpIkifKLRehiA+n98/2EdIhzW6/8RAba\n6CBUge6tiWyVRhQ6z3TgkxBG1UX3m2z6pDBUQXqKDqQ1OF5BELhpalfOb7zIxZ059db1C1bz9ILW\nnNlTzMbFnuv2uy2AVz4MZerEHLau92yZEhqqYNHPwURGiowcUciF8+4l6qAgkZ8WhnBTdw0DhuSy\ne497qV8QBO5/QM/szwJ4dlIJ018r5rnJJXzwtmepPi5JxYPPh/PT9hS+XJNEUgstX03LIP1Mpdv6\nUU38uHdmG5Y+v5fc1Ppjx0R1iaHRsCacWriv3nrg2AjtlkzRjivL8XpVuDo1SxfgjCRJFyVJMgOL\ngRFu6k0ClgK1l5MCl8GjbyhmLhlMaPQiGqUFjdKCWmmtLkqMlB68SESXWDQKCxqFBZ3SXKdoFTXF\nVlDCiR+P0HlCK3RKMz4KExrBXFPEmqIVZEW0F71oRC8a+XvBJZZ/lcOHP8XTpKlYfVwrWGTFWl1M\n5VZu6ZnL7A/LObbfzF0jCrhntI5ZHwbir1GgFexFQ01xHntyUjEDhuSRm25jzNhCzp+3sun3SNo2\n01bX0QoiWkFEAyz4qoIF8yqZ/20gd96uRSNIsrHUjM85Zvu4TWgFk+sxsea+tYKZI2sucWF3LvfN\nbo/ex+Yybz4Kk6yY8XHMd+6mU/gnBDLo5zH4B4guz8X5zDQKC+X7zxLcOQG17Bk7n7lGaUE0VKL2\nVaNVWqqL/Lx/cgiGtDxHWwtqpcWl/4ThzSndc9YjXfjISlCwwIBpnfnrnT3YSso904VoJjpGwbhX\nEljzZQY7lmZ6nMu+/dTMWRjGR6/ns+KH0urnoREkx/MR0AoC/hqRj98PYuKDeu64vZDtW81u6UKv\nVDL9+SDmfBDCI08U8vOPVXXoxkkX/Xv6MPODAH5cZMBoBKsV/t1oaJAuWjaDL9ckcfuDQXw88QTl\nGaVu6aJVd39undqcn5/YiSGvzANd2Oe24/3NSf/rDJVnstAq6r6rcrqI7NmIkp2nq5+nO7qQ08O1\nwlVmGooB5LqkdMexmv4FIRoYKUnSl1Bn+S0BGwRB2CMIwsSGxnpDMXObwYxC617PW3YiC21UAOpg\n723Dd8/ZR/M7muAfe3m6bTnWfZ/H30sLmLk4gehE74JRrV5VhSDAV19VMOaeAmZ8EMBjj/g2KN1m\nZFr4e0sVaekWOvTOolN7FUu+CyUo0GGlYJKqpSyjUeK5KSWsXFnFrFmBtG9/bbIFARzbWsCKGanc\n/kYrfEO88461Gi0c/GIPHZ7u6nZTUw5DdglBnT2vsCQJ1OGeIzhqowNR+GqxVrqXUqP7NSFj/UkM\nefWnb3MioUcULQfHsWb6/gZTooXHa5n+fQpLZmWzabnnuNwt2qiZvzSC776u4JMPSuvt94HxehbM\nC+LJZwv5Yl6Zx7qDB/iw9tcIvpxfxrMvFWIy1a1ntUo8+1xxteVHRYXEl597Nw8Aj7wayciJEUy/\nN5XsNPfz225YNF3HxLPoib0Y64mJrtaraD2hA/tn72pwXoM7JVB2MgtzWcNpAa8pPEjipVmpZBxY\nX12uAp8Ccl26/OW4SZKkDsBQ4ElBEHrW19ENxcytRjOiB2ZetOcCQZ0Sve4r71A2WftzaPdAqyse\nz5+L81m9II/pC5Mvy4b82/mVGAxgMtslo6pK77bDP/u6DIsFzGaw2ew6QoXMNvyRSYXcOiqP7BwL\nd44poLxMYuWKEGKir10287OHyvjhpRNMnNOaiBTvP4Knfj1OYEowER3r35yuyiym+MBF/Ft4rmfK\nLaG+756oVCCIAhVn626CAqh8NUQPaMrFld6HaO35aDMqC43s8uCmL0d0oobpi5L56aMsNq707HwT\nl6Dk5xUh7Nhm4qXnSjCbPdNBt64a1q8KZ9mqSl6aXozB4L5uoyQVG1ZFkJVt5faxeRQUWlm2soKb\nB+Zgs0koFAJffB7EveN8iIoSEUU4eMDCqt88W8XUxpD7whg5MYI37kslN809c7354Uak9Ahl3VsH\n62XUycObYiyqIuOf+tVeCh8VAW3jKNrlOWrj9YAnSTwgIoXYtoOqiwdkAPGy/8c6jsnRCVgsCMJ5\n4E7gc0EQbgOQJCnL8TcPWIFdbeMRNxQz94kKQOurRKWwolJYUSss1cWUXUh4lzi0Ckt1USusNUW0\nUHUxj73vb6XiQh77Pt7OTU+3w9dXQCNa3BYXNUmt5eThP3P5dXY2by+MJzpKcKmrEmyoBJuLakUl\nSKgEiVNHTZw9a9/o0uvtHOnwQYvL0lkliKgEEY2grC7lJRJfflOG1Qo6nYAA/L6uCjUKNIKSglyJ\nPzZUceiIie69crm5u5bv5gUTpFeiEUTUglBdnGNxHZ9NNm7391xwrpTZj5/kwfcb07yjzuWePc2h\nRrRgKSrj4vozdJncEbVocS2O5+N8ZkX/nib8pmS0ahsa2fN1PnOVwoqtvAq1vwalwlpd5OfVCgv+\nTcKpSs2sXqbXpovGd7Xi0pqjiCZDnTG5uwedxsbomR3YvSiVjH15deeolhoupbGCdxbF8837OWz/\nvajW/NbMe0SoyI9LglAr4YmJxRjKJDSCWFNkdJEcp2bdr+HkZNu4bXQeRXmgRIESBVjE6t9h/mqW\nfRtJ905aeg7I4cnnijhz1sL2f+x0dktvHz79IJgje6PYuTOcHj1UPDu5hOMHjV7TxcjxAdz5SCgf\njD9GaUaZi/pRK1jwEa3c+lQSBWdLOLbynOd3TG2j89OdOPjZLpQ2kwtNyOlCq7AQ2asRRdtPe6QL\nOT1cM1ydznwPkCIIQoIgCGpgDLDKpXtJauQoSdj15k9IkrRKEASdIAi+AIIg6IGBQL0mPTcUM2/9\n8T0ofesu620mC3nbz+HfrP6ATKUXijmz5gyr7l1FeWY5gYlXliD52K5S5k+7yPT58UQneh+EKy/P\nyphRBahUcP/9Pny/IIRzJ6J5c1pA/eMus9Kyh92rceyder7+JIwTO+M4+m9ctWrmi29KsVnBaLRL\n7mGh4jXb6AS7N+t7D59h7AuxtOlzed6x2z7aT0y3GAIS6r9PgOwtZwm/OaXeOpZyo1s6kMOvSQRl\npz1vRPrGBxLUIoKLf3qf3iwwSsfIt9vx/fNHKM0zYqiwkHbcs4oivrGWDxfG8NmbeWxc53mzU6cT\neft9f6JjFNxxRwEZGXadr9EoUVbLNlyvU/Dj3HAG9Pah59BMDh4x8v0vZTTqeMklaqIoCjwwxo/i\nEgmjEQwGiVlf1N2UjIlW8OsvocybF8iEB4rY9Lf3aoxh9wVzx5NRvP9wKmVFdfXUaq2Cu2Z25K9Z\nJ8l1k5ijegzdY9BH6kldcaLe64V0TaAqqwTJ+n8X2epqdOaSJFmBp4A/gWPAYkmSTgiC8KggCI+4\nayL7HQFsEwThALATWC1J0p/1jfWGYuaeUH4uD11MIMp6LF3A7uShVCuRLBKmMhO/jPuDkkuXl9My\n7UQ5syafY/KnjUhp5b3DTX6elfH3FNKkqZJTJyN4951Abu6pQaOpn+FeuGSmz22ZtGymIedEAgtm\nhzNquJ7oyBqr0qoqK5/PK8NsAbUKFKLAx5/Vr4e9HJSVWHnv4dMMHBtG7zsuLynAhW0Z5BwtoN3E\nhmPlVOWWU5FeTFB791YuTljKDSj96rcY8msSQfkZ92oWJ5LvasPpJUcva54a9wyn26gYvn36EDNv\n38EnD9bfvlEzDR8sjOaz94v5Y4Vnxq9UCrz7jj933uXD4Nvy2H/QyO2j8xg9vq5VjigKvP58EDOm\nhzDoziyefCGf0lIbS1a69v/yW4VYrRLOKND/bDeSlu5ehz1ksA9ffxfEyy+Wsmyx98lO+o0Oo2P/\nQGY+nuqSv9aJsEZ+DHy2Ob88v9dtHBuwW9p0ntyZY98ewFRPqFxNsC82k5Wy1MuPinmlEGySV8UT\nJEn6Q5KkppIkNZYk6X3HsbmSJM1zU/chSZKWO36flySpnSRJ7SVJau1sWx9uKGauEq0oBFt1UYr2\nUn4yi8AWkdX/ry5CraIEm8W+BFNqFQx6qyshCTqUohWV4CiipaYI8mKl6FIFcx45xiP/iaV9Dx0K\nbNVFXleNFTU1qpXsS2buvqOQoUO1rFodgl6jQCUIqBBriqCoLs7l8o7dRvoMz2LCvQFsXBZLoK8a\nlaCsLgpBxGyENjdnYjJD7x4a3psWzMZVkZzZG4daUMj6F6rL7u1GKktt1eNTCVL1mO3jtt+HAhvG\ncjNzp2fS4WY/7ngktHou7EU2Py7zZj8vVRnZ8t4eBrzWER8fsXq5Xue5OJ5l3rZUInokoNYIdZ6l\n/Llby6vQ+qtRidbqUpsu/JMCMeSWgsHgkS6iOkeDJFGwP8NFnaAUrdXFHV207h3IpSOlFGYYMBls\nFKdXusxFbbpo3kLJrK9D+Oz9Ylb/XOIy7yqB6qIWRSY95sd7bwQy7PZ8Dh42s/+gmfNnbS50oRBE\nFIJI1/ZarDb73ovBKDFjVonL+R++iGD1T5FMeTKApilKbDboOzQXUwVu6aJzBzW/Lg1m3mflzJ1V\nihKbR7qQ39/4FyIIiVDy3dRTKCRLHbrofEcUMc392fzhAVSCtdb82uc8omkgSYOTObvsWB26kJfg\ntjGUHL7kli7k9HDN8D8P0P9blB63M/OGYDFYsJpsaIO0jPh2KM2HJXp9jfJiM4vfv8BtT8TSfUig\n1+1OHDczdlQBEybqeW6Kn9eu/QsXlzH64Wy++TScSRMC3UF5CpkAACAASURBVLbLy7cyaHQmfnqB\ni4fiWL80micfDqBtK43LxqgcP/5cweSnSkhPb5jgDZU2pj18Ca1O5L6p0ZcdlmDLZ8eJ7RxOfLeG\nnw1A1pazRPd27/Uph7msYTWLqFTgmxRK6RnPUpwgCDQf24q0jee9Gh9AUWYVn953AJtVAsnutXtq\nT8P5OJObqJi/JIz5n5Wx8Jv6Jd/0DCuCACYTmMwSs+a630T9+MtiDEYJrdb+XC5csrBhc40NuI+P\nSJ+bfHjr5WAObY3jxK5otBq47e5ciks8BP5qpGTJihD+/tPA7I/KPXqgyiGKApM+jKcox8TSj+pu\nZAqCwIhpLUnbm8+xde6DoAGkDGvMqV+PYzV6Ni0MbhdD0WH3eUivB26keOb/v2DmJSeyCWzRcAKD\nvEPZqHxV3L18JMEp3idfsFkl5k5JJTRWQ7+x3jEmgN07jTw4tpCXp/kz/n7vQt9arRLvflLEB3OK\n2bgihoF93bc7etJIj6Hp9O7hw4FNcYSH1u/MK0kSM2aW8umccn5dFkzLlvVb3xiqbEybcInoBDWT\n3o68bP17xuFCjq9P5+bnvAtFbCiowFxuIqxz/SoWAKvB3KCaBSCkUzzl5z2bBwIkDUwmfdsl8o55\nl50oIFLLmDeaEJbgg0ojYjFJ/PVDtldt4xOVfLMkjB++q+DLOZ5VLouXVYIEOp3damnR4nKKS+p+\nfD95O5T9f8Xz8X9CGXaLDqUCho/P5NAx96qKhDg1J3bF0aWjhoEjcriQ5p5phoUrWLg4mJ3bjfzn\nxSK3oXlrQ60RefrLpuzbUMi2JXVd+jV6JSM/6EJ9YmxgcjDBTUJIW+/ZYijIwcwlLz4y1wT/k8yv\nD0RBcllyiYKEpaQCc0kVfvFBiEiIgvsiWSykbbrI8C8GoPVTIgo2FIJUXZz1FNQU57F1n53DYrJy\nz4vxiNS0E6kptdvt3lbFB++UMXN2AEOH+6BAqC6io9RGRaWNsRPz2HvAxL9rYmnRWIvo+CfHmg3l\n9B+VwZtTQ3j7pTCUYs3SWiHUfaRms8Qzz5WwcZORP1aF0biRCkWt68vnymywMnVCDuHRSp59LxKl\niOtcYbMXD/MmWayse/MAt0xphW+Q2jG/Nlmp+3wy/jxFYJNQVFqFy7w6zzufuWAxYTNaUPooXNrX\npgtRkPBNDKZgz8V66UKlVdD6gTbsm3ewenz10YVKhB6jopj+Rxcmf9eWqEZa0o5XkHfJUC9dOPuJ\njVPw49IQVq+s4uMZpYgSdeji3w2R7N8WxawZwYwarkMAWt+UQWWFhEIQq2lCKSpo2VTDo+MD+W1R\nDBUXkhncV8eQMVnsP2hCRKxDFwqFwHv/CeLh8b4MGpnDwQPm6us6xwHg76/gmx+CycywMG1KITar\nreZe5Pcnmyv/IAXPz2/Kus8vcOKf/Dp0Ed0igNZDY2vNrytdtLy3FacXH0KQ3NAJEroQHSp/LZUX\n8z0+d3loh6vFVToN/Z/ihmLm7mAuNRIzrFWDjijn1qYSkBRIWIv6o/rVxsENeexalcOTnzZGofQ+\nlvjUSUVMfdWPnjc3LEECZOdaGDQqG38/gV+/iSQkuK5tuCRJzJlfxOMv5vLboijGjWrYGqe0zMZd\n4/MoKLSx8tdQwkLrtzk3GiSmTswlOFTBlBlRHtU19WHbvFPEtQ+m5dC6MTzcQZIkLv5+goRbmzdY\n11xShcpfi+hFbteg1tEUHmlYiku5rQlF50vIPuT9xpogCDRqH8CMP9py72sJvD3hPOWl3ulqwyMU\n/PBLMNu2Gpk5s9yt5Bsbo2T0HXq+nxtO5ol4kuKV9BmRQUaWZxWEKIr8tiiGL2eEc+u4TJau8by5\n/+hDfnz6fjD3jC9gzVr37vk6nchn34ZQVGDjpUlFWOqxg3ciIl7LxNktWfpuKnlp3tuuOxHZMQql\nVknWds9JL4LbRlN0sP6AXtcMkuRd+S/ADc/M9fFBNH28V711bBYbRxcdps2Dl5cTNPtsBT9PO83E\nWS3xD/HOKWjX1ipeerqIT+YF09lNCFp3OHHKTJ9hWQy9Rce8T0NRq+syUKPRxoTnclm1voJ/V8fR\nrWPDljSZ2RaGjsolMV7Jom+C0evqf9xGg41nHy3AL0Bk2kehDTLyytK6lhFnduRzcMVFej3ezGsd\ne8HRHJAguE3DKixTcRXqQO9UVtpwv/+PvfMOj6Jq//5ntmdTN41UQhJ6770IKE1ARFGaChYUEQT7\no4gNFRQRUVRERAQVEQtSxAKCIEUU6T0QIL233Wyf94/dzU6Sze6G4u/hvZ4v17my7JwpO+eee+7z\nPXdBGaii4qL3PEVypZyO97Xmr6X+V8GR4qa7YmjfO5g3pqX7pfAAwiPkfPpFOPv2mZn6cN1BQABB\nQTJ2bIpl7K3B9B6ewd+HvLsP3josiC1r4njyxQJee7u4Tm+boYMC+OrzCFZ/aeCTTz3TPgEBMt75\nOAJjpZ1nH87DbPL9+1I6hHLDXQl8/OgxLMb6LUYKgkCzce04+XndY5EwuDnaeN9urlcD/+PMrzHy\nd5/DVOi/+1TWnouENAolur3/hYGNFVY+euQotzyRQlIb//zR9+6o5MVZ+Sz6KJyOXf1T5L/9bmT4\nmDxeeFrHs4/VtdBpZfCdmRSX2Pju0zgaJvh+sRw8YmLwLXlMuDOQt+fpUPiYVRj0dmZOKSIpWcGL\ni6J89t+7qZBFdx2stkBWXmBi7bNHGDm3E0ER/s1IAM5vOEnS8BZ+KX9LSSXKMP9dQnVt4yg65NuK\nazo8lfLMCrL+9p5Qqy5Mfi4OlVpg6ZwM7Hb/nu6QUDmrVzt89idOLKK01M73PxiY/3btBU9BEHjy\nER0LX45k2PgsvtvsPQS/QxsNuzclsvEXPZOm52IweFaq7duqmDc3jA+WVfDmm55TBag1Am9/FIEg\nE3jmoTzMHlwQa6Lv+DgaJGtZ/5p333FPSBiQgiG3wvGS94DwdvFEdmtU7+NeDv5Hs1xjnPt0D6YC\n//NJnFlzmNRhTfy2FEVRZPNbJ2nSTUfP22L92mf3bwZeeiyf+R9F06GLf4p81ZpyHpheyMqlEYy7\nLchjn2OnTPS4+RK9ugawbnksQYG+h2zDFgMjx+Xy8uwwpt7n2YNGFMWq8PGSYjtTJhQQFS3n8dmh\nPhX5yf1lrHolnXveaFG1MGq3i3z1n8N0HhVPcvcor/tLYdGbydhxnsQh/mWtNJdUogzxX5mHt42n\n6JBv7we5QkbHB9rw19JDl+WfL5cLPP5OEiajnZUL/VtMBdBoBD54P4wWLRQMGJrHI7OKWfhuGUXF\nnpXvrTcHsfmLOB6dnc/iZXVb3QCxDRRs/SaOqAgFg+7IJjff8zEbJSnYvD6Kbb+ZePrpUo9ZFJUq\ngVffiyIuUcHrM7OweMj7IoUgCIx/uSnpB4r5+/v6USIyhYxm49uRtt57ib9/Bf+jWa4N7KKA1S7D\nVGRAFhaEXRTcDWcTq7eS9BLKLpQQ3yfJ+Z2sqtlEoaq5+tsQ2Pt1BhnHyhj9TGPJ8auW/dz7OM/5\n9x96Xn6igHnLGtCqU0DVPlLYEN1NtDPvrVK2/GLkx2+i6d2juhVrE+3YRDubt5Yz8LYM5jwRzqvP\nRtbyKLFL/tlEO1a7jQXvFzPz2UK+Xd2AW0doJX3FqmZD5Is1Bm7snceZUxYmjimkXUc1L7yhQyaX\nYcNxH+yS5vrN6adNvDfjLFMXNiW2aXDVb92+/Dxmo53+05pUu//u+yuTNPf2i7+eI6pDHCpdYO2x\nlIyn1S5zjH2JEWVYQK1xdm232qsfP6xdPEWHM7E5c9nU3WSkDk5FHaImbWeOR7moui/V5M4tEyqt\ngknPJfDHLxV8vqTQcd887FNTLpDDfVO05OTYMBodzhErVteeebrkokM7Fbs2xrPxVz2TZuRWi/ys\nKRcqDbw+R8eAPgHcMDyb46fMNfo6ZCIiUsaatTouXLIx46FijJVi1TPnaoJSxvTnI7Db4fVZWVis\nVH+GXM+Is78qUMm4tzuwccFJMk9X1JIJb3IRP6AxmTvSMVVY/JKLmuN+tfA/y/waQrSLWOrBm55f\nf4JGw5ojV/qXbKrggp6fF59mzOvtUKp973P0TwPzHs1i/rIGtO7om1qwWkUee7KUX7eaeHteOE0a\n16ZMRFFk8UclTHk8n3UrYpk4xndCK7NZZOoTBXz5TQU7NsTSuX3dswNRFHlnUQW5OXZGDS1gyM1q\nHpsd6nPmUpRr4dX707jz6SRa9nRzluf+KWXXqnTufKMdckX9RCrrj3SSR/he+HTBXFqJ0kfpQCm0\n8aEoAtXoM337gssUMpqPbspv8w/UGa3oC6ERCl5f1ZBfvynlm49rl1mrC1MfKsHiXIIwmWDRkrrz\njAMkxCn4dkUMJrPIgNsyyc71tjAq8MJTOuY8FcbQ23P4dbvnhcmgIBmfrtShVgvcO7GIMg++6Aql\nwH8Wx6Mvs7PoP9k+/dBjmgQz7MkWfDHrH0z6ujMo1oRGF0BUx3iytvmfbuGa4H+uidcOlnIjcq0S\nmR/K2WaycuGn0ySP9E9Z2K12vn7mEAOmNiY61TPtIcXZY0ZemZbB04vi/VLkBoOd++8rITvHxrdf\nRxAdVfs3mM0i054qZP8/ZnZuiKdnF9/HLSq2MXx8DgWFdratjyUh3rvP+d49ZgoL7djtjhnimdO+\nF6kqK2y8dv85brozkl6jqtMo+3/IYfSLrQmLrV890dx/silLL6ZBN9++5VUQRTQN/M/WKAgCoc2i\nyf/TdzEKgMQe8TRoFc7+T+rP9boQEa1k3uqG/PBZMd+u8v0SAXjllRCmTwuiTWsFCgWUlYuMv9e7\nd41WK+PLD2MYNlBL92GXfC6MjrstiC8/jmbqzCI+XumZplSpBN56N4yWrRU88WgJ+bm1ZUOllvHC\n0gQy082smJvpk5bqeEs8zftFsePd+tEmjYY35+Lmyx+Hq4H/WebXCBa7HGOhAaUuEJsoqzbF8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iDVOgd/apucAJoLc7qKWj+w28PC2LO2c0YOiESMf3djDY3dRTud2tRCtsmqq/OxcfpuCSkWHv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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d98e950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "jx_fct = lambda x, y: -np.sin(2.*np.pi*x)\n",
    "jy_fct = lambda x, y: -np.sin(2.*np.pi*y)\n",
    "\n",
    "jx_vec = jx_fct(mesh2D.gridFx[:,0], mesh2D.gridFx[:,1])\n",
    "jy_vec = jy_fct(mesh2D.gridFy[:,0], mesh2D.gridFy[:,1])\n",
    "\n",
    "j_vec = np.r_[jx_vec, jy_vec]\n",
    "\n",
    "print(\"There are {nFx} x-faces and {nFy} y-faces, so the length of the \"\n",
    "      \"face function, j, is {lenj}\".format(\n",
    "        nFx=mesh2D.nFx, \n",
    "        nFy=mesh2D.nFy,\n",
    "        lenj=len(j_vec)\n",
    "     ))\n",
    "\n",
    "plt.colorbar(mesh2D.plotImage(j_vec, 'F', view='vec')[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### But first... what does the matrix look like?\n",
    "\n",
    "Now, we know that we do not want to loop over each of the cells and instead want to work with matrix-vector products. In this case, each row of the divergence matrix should pick out the two relevant faces in the x-direction and two in the y-direction (4 total). \n",
    "\n",
    "When we unwrap our face function, we unwrap using column major ordering, so all of the x-faces are adjacent to one another, while the y-faces are separated by the number of cells in the x-direction (see [mesh.ipynb](mesh.ipynb) for more details!). \n",
    "\n",
    "When we plot the divergence matrix, there will be 4 \"diagonals\", \n",
    "- 2 that are due to the x-contribution\n",
    "- 2 that are due to the y-contribution\n",
    "\n",
    "Here, we define a small 2D mesh so that it is easier to see the matrix structure. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Each y-face is 3 entries apart\n",
      "and the total number of x-faces is 16\n",
      "So in the first row of the faceDiv, we have non-zero entries at \n",
      "  (0, 0)\t-3.0\n",
      "  (0, 1)\t3.0\n",
      "  (0, 16)\t-4.0\n",
      "  (0, 19)\t4.0\n"
     ]
    }
   ],
   "source": [
    "small_mesh2D = Mesh.TensorMesh([3,4])\n",
    "\n",
    "print \"Each y-face is {} entries apart\".format(small_mesh2D.nCx)\n",
    "print \"and the total number of x-faces is {}\".format(small_mesh2D.nFx)\n",
    "print (\"So in the first row of the faceDiv, we have non-zero entries at \\n{}\".format(\n",
    "        small_mesh2D.faceDiv[0,:]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, lets look at the matrix structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Ko3LmdMgQ+OpXYcWKoNZ88mS4/np49tngi1bPPx9sSx05X/OQPaePPx58GvHK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\nJwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10dd33890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,2, figsize=(12,4))\n",
    "\n",
    "# plot the non-zero entries in the faceDiv\n",
    "ax[0].spy(small_mesh2D.faceDiv, ms=2)\n",
    "ax[0].set_xlabel('2D faceDiv')\n",
    "small_mesh2D.plotGrid(ax=ax[1])\n",
    "\n",
    "# Number the faces and plot. (We should really add this to SimPEG... pull request anyone!?)\n",
    "xys = zip(\n",
    "    small_mesh2D.gridFx[:,0], \n",
    "    small_mesh2D.gridFx[:,1], \n",
    "    range(small_mesh2D.nFx)\n",
    ")\n",
    "for x,y,ii in xys:\n",
    "    ax[1].plot(x, y, 'r>')\n",
    "    ax[1].text(x+0.01, y-0.02, ii, color='r')\n",
    "\n",
    "xys = zip(\n",
    "    small_mesh2D.gridFy[:,0], \n",
    "    small_mesh2D.gridFy[:,1], \n",
    "    range(small_mesh2D.nFy)\n",
    ")\n",
    "for x,y,ii in xys:\n",
    "    ax[1].plot(x, y, 'g^')\n",
    "    ax[1].text(x-0.02, y+0.02, ii+small_mesh2D.nFx, color='g')\n",
    "ax[1].set_xlim((-0.1,1.1));\n",
    "ax[1].set_ylim((-0.1,1.1));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How did we construct the matrix? - Kronecker products. \n",
    "There is a handy identity that relates the vectorized face function to its matrix form (<a href = \"https://en.wikipedia.org/wiki/Vectorization_(mathematics)#Compatibility_with_Kronecker_products\">wikipedia link!</a>)\n",
    "$$\n",
    "\\text{vec}(AUB^\\top) = (B \\otimes A) \\text{vec}(U)\n",
    "$$\n",
    "\n",
    "For the x-contribution:\n",
    "- A is our 1D differential operator ([-1, +1] on the diagonals)\n",
    "- U is $j_x$ (the x-face function as a matrix) \n",
    "- B is just an identity\n",
    "so \n",
    "$$\n",
    "\\text{Div}_x \\text{vec}(j_x) = (I \\otimes Div_{1D}) \\text{vec}(j_x)\n",
    "$$\n",
    "\n",
    "For the y-contribution: \n",
    "- A is just an identity!\n",
    "- U is $j_y$ (the y-face function as a matrix) \n",
    "- B is our 1D differential operator ([-1, +1] on the diagonals)\n",
    "so\n",
    "$$\n",
    "\\text{Div}_y \\text{vec}(j_y) = (\\text{Div}_{1D} \\otimes I) \\text{vec}(j_y)\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\text{Div} \\cdot j  = \\text{Div}_x \\cdot j_x + \\text{Div}_y \\cdot j_y = [\\text{Div}_x, \\text{Div}_y] \\cdot [j_x; j_y]\n",
    "$$\n",
    "\n",
    "And $j$ is just $[j_x; j_y]$, so we can horizontally stack $\\text{Div}_x$, $\\text{Div}_y$\n",
    "\n",
    "$$\n",
    "\\text{Div} = [\\text{Div}_x, \\text{Div}_y]\n",
    "$$\n",
    "\n",
    "You can check this out in the SimPEG docs by running **small_mesh2D.faceDiv??**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# check out the code!\n",
    "# small_mesh2D.faceDiv??"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have a discrete divergence, lets check out the divergence of  the face function we defined earlier. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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HxXcvZuJFEznxoeMYOnsIyh5m/G79fB3b7nwFpGTIXVeTdcjktA3DW1d+RfNX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DOp8WpUOdB4OIOGRiYaBasJn0mvoYGYcbDD1OYMpaGxYtG4FH1IDY1Pjb00eUQ0Hp8mRVOTaBhs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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110b8f850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Div_j = mesh2D.faceDiv * j_vec\n",
    "\n",
    "fig, ax = plt.subplots(1,2, figsize=(8,4))\n",
    "plt.colorbar(mesh2D.plotImage(j_vec, 'F', view='vec', ax=ax[0])[0],ax=ax[0])\n",
    "plt.colorbar(mesh2D.plotImage(Div_j, ax=ax[1])[0],ax=ax[1])\n",
    "\n",
    "ax[0].set_title('j')\n",
    "ax[1].set_title('Div j')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Are we right??\n",
    "\n",
    "Since we chose a simple function,\n",
    "\n",
    "$$\n",
    "\\vec{j} = - \\sin(2\\pi x) \\hat{x} - \\sin(2\\pi y) \\hat{y} \n",
    "$$\n",
    "\n",
    "we know the continuous divergence...\n",
    "\n",
    "$$\n",
    "\\nabla \\cdot \\vec{j} = -2\\pi (\\cos(2\\pi x) + \\cos(2\\pi y))\n",
    "$$\n",
    "\n",
    "So lets plot it and take a look"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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V1micAVBlzTqcAdzfucYZAFXWxJwBMI812fdbY83cbVoS1iicAVBljcaZJFVY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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d960210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# from earlier\n",
    "# jx_fct = lambda x, y: -np.sin(2*np.pi*x)\n",
    "# jy_fct = lambda x, y: -np.sin(2*np.pi*y)\n",
    "\n",
    "sol = lambda x, y: -2*np.pi*(np.cos(2*np.pi*x)+np.cos(2*np.pi*y))\n",
    "\n",
    "cont_div_j = sol(mesh2D.gridCC[:,0], mesh2D.gridCC[:,1])\n",
    "\n",
    "Div_j = mesh2D.faceDiv * j_vec\n",
    "\n",
    "fig, ax = plt.subplots(1,2, figsize=(8,4))\n",
    "plt.colorbar(mesh2D.plotImage(Div_j, ax=ax[0])[0],ax=ax[0])\n",
    "plt.colorbar(mesh2D.plotImage(cont_div_j, ax=ax[1])[0],ax=ax[1])\n",
    "\n",
    "ax[0].set_title('Discrete Div j')\n",
    "ax[1].set_title('Continuous Div j')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Those look similar :)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Order Test\n",
    "\n",
    "We can do better than just an eye-ball comparison - since we are using a a staggered grid, with centered differences, the discretization should be second-order ($\\mathcal{O}(h^2)$). That is, as we refine the mesh, our approximation of the divergence should improve by a factor of 2. \n",
    "\n",
    "SimPEG has a number of testing functions for \n",
    "[derivatives](http://docs.simpeg.xyz/content/api_core/api_Tests.html#SimPEG.Tests.checkDerivative)\n",
    "and \n",
    "[order of convergence](http://docs.simpeg.xyz/content/api_core/api_Tests.html#SimPEG.Tests.OrderTest) \n",
    "to make our lives easier!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "uniformTensorMesh:  Order Test\n",
      "_____________________________________________\n",
      "   h  |    error    | e(i-1)/e(i) |  order\n",
      "~~~~~~|~~~~~~~~~~~~~|~~~~~~~~~~~~~|~~~~~~~~~~\n",
      "   4  |  8.86e-01   |\n",
      "   8  |  2.96e-01   |   2.9914    |  1.5808\n",
      "  16  |  7.90e-02   |   3.7462    |  1.9054\n",
      "  32  |  2.01e-02   |   3.9364    |  1.9769\n",
      "---------------------------------------------\n",
      "That was easy!\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 0.026s\n",
      "\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "import unittest\n",
    "from SimPEG.Tests import OrderTest\n",
    "\n",
    "jx = lambda x, y: -np.sin(2*np.pi*x)\n",
    "jy = lambda x, y: -np.sin(2*np.pi*y)\n",
    "sol = lambda x, y: -2*np.pi*(np.cos(2*np.pi*x)+np.cos(2*np.pi*y))\n",
    "\n",
    "class Testify(OrderTest):\n",
    "    meshDimension = 2\n",
    "    \n",
    "    def getError(self):\n",
    "        j = np.r_[jx(self.M.gridFx[:,0], self.M.gridFx[:,1]),\n",
    "                  jy(self.M.gridFy[:,0], self.M.gridFy[:,1])]\n",
    "        num = self.M.faceDiv * j # numeric answer\n",
    "        ans = sol(self.M.gridCC[:,0], self.M.gridCC[:,1]) # note M is a 2D mesh\n",
    "        return np.linalg.norm((num - ans), np.inf) # look at the infinity norm \n",
    "                                                   # (as we refine the mesh, the number of cells \n",
    "                                                   # changes, so need to be careful if using a 2-norm)\n",
    "    def test_order(self):\n",
    "        self.orderTest()\n",
    "\n",
    "# This just runs the unittest:\n",
    "suite = unittest.TestLoader().loadTestsFromTestCase( Testify )\n",
    "unittest.TextTestRunner().run( suite );"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks good - Second order convergence!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Next up ... \n",
    "\n",
    "In the [next notebook](weakformulation.ipynb), we will explore how to use the weak formulation to discretize the DC equations. "
   ]
  }
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